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senior lead machine learning engineer

Capital One

<div>Senior Lead Machine Learning Engineer<p></p><p>
As a Capital One <b>Machine Learning Engineer (MLE)</b>, you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.</p><p></p><p><b>
What you&rsquo;ll do in the role:</b></p><p></p><p>
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:</p><ul><li><p>
Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.</p></li><li><p>
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</p></li><li><p>
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.</p></li><li><p>
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.</p></li><li><p>
Retrain, maintain, and monitor models in production.</p></li><li><p>
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</p></li><li><p>
Construct optimized data pipelines to feed ML models.</p></li><li><p>
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.</p></li><li><p>
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.</p></li><li><p>
Use programming languages like Python, Scala, or Java.</p></li></ul><p></p><p><b>
Basic Qualifications:</b></p><ul><li><p>
Bachelor&rsquo;s Degree</p></li><li><p>
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</p></li><li><p>
At least 4 years of experience programming with Python, Scala, or Java</p></li><li><p>
At least 3 years of experience building, scaling, and optimizing ML systems</p></li><li><p>
At least 2 years of experience leading teams developing ML solutions</p></li></ul><p></p><p><b>
Preferred Qualifications:</b></p><ul><li><p>
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field</p></li><li><p>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</p></li><li><p>
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow or TensorFlow</p></li><li><p>
3+ years of experience developing performant, resilient, and maintainable code</p></li><li><p>
3+ years of experience with data gathering and preparation for ML models</p></li><li><p>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</p></li><li><p>
3+ years of experience building production-ready data pipelines that feed ML models</p></li><li><p>
Ability to communicate complex technical concepts clearly to a variety of audiences</p></li></ul><p></p><p><b><i>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.</i></b></p><p></p><p>
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.</p><p></p>
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer<br>
<p></p>
McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer<br>
<p></p>
New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<br>
<p></p>
San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<br>
<p></p>
San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<p></p><p><br>
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.</p><p></p>
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<p></p><p>
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</p><p></p>
This role is expected to accept applications for a minimum of 5 business days.<p></p>
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.<p></p><p>
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.</p><p></p><p>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com</p><p></p><p>
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.</p><p></p><p>
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p></div>

Senior Lead Machine Learning Engineer

Information Technology Senior Management Forum

<div><div><p>Posted Date</p>
<p>4/10/2026</p>
</div><div><p>Description</p>
<div>Senior Lead Machine Learning Engineer<p>
As a Capital One <b>Machine Learning Engineer (MLE)</b>, you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.</p><p><b>
What you&rsquo;ll do in the role:</b></p><p>
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:</p><ul><li>
Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.</li><li>
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</li><li>
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.</li><li>
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.</li><li>
Retrain, maintain, and monitor models in production.</li><li>
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>
Construct optimized data pipelines to feed ML models.</li><li>
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.</li><li>
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.</li><li>
Use programming languages like Python, Scala, or Java.</li></ul><p><b>
Basic Qualifications:</b></p><ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>
At least 4 years of experience programming with Python, Scala, or Java</li><li>
At least 3 years of experience building, scaling, and optimizing ML systems</li><li>
At least 2 years of experience leading teams developing ML solutions</li></ul><p><b>
Preferred Qualifications:</b></p><ul><li>
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow or TensorFlow</li><li>
3+ years of experience developing performant, resilient, and maintainable code</li><li>
3+ years of experience with data gathering and preparation for ML models</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
Ability to communicate complex technical concepts clearly to a variety of audiences</li></ul><p><b><i>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.</i></b></p><p>
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.</p>
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer<br>
<p></p>
McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer<br>
<p></p>
New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<br>
<p></p>
San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<br>
<p></p>
San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<p></p><p><br>
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.</p>
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<p>
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</p>
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.<p>
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.</p><p>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com</p><p>
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.</p><p>
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p>
Senior Lead Machine Learning Engineer<p>
As a Capital One <b>Machine Learning Engineer (MLE)</b>, you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.</p><p><b>
What you&rsquo;ll do in the role:</b></p><p>
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:</p><ul><li>
Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.</li><li>
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</li><li>
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.</li><li>
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.</li><li>
Retrain, maintain, and monitor models in production.</li><li>
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>
Construct optimized data pipelines to feed ML models.</li><li>
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.</li><li>
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.</li><li>
Use programming languages like Python, Scala, or Java.</li></ul><p><b>
Basic Qualifications:</b></p><ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>
At least 4 years of experience programming with Python, Scala, or Java</li><li>
At least 3 years of experience building, scaling, and optimizing ML systems</li><li>
At least 2 years of experience leading teams developing ML solutions</li></ul><p><b>
Preferred Qualifications:</b></p><ul><li>
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow or TensorFlow</li><li>
3+ years of experience developing performant, resilient, and maintainable code</li><li>
3+ years of experience with data gathering and preparation for ML models</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
Ability to communicate complex technical concepts clearly to a variety of audiences</li></ul><p><b><i>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.</i></b></p><p>
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.</p>
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer<br>
<p></p>
McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer<br>
<p></p>
New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<br>
<p></p>
San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<br>
<p></p>
San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer<p></p><p><br>
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.</p>
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<p>
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</p>
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.<p>
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.</p><p>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com</p><p>
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.</p><p>
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p></div>
</div><div><p>Salary</p><p>
229,900.00 - 262,400.00 Annual</p>
</div><div></div><div><div><p>Type</p><div><p>
Full-time</p></div></div></div></div>

Enigma

<div><h3 class="jobSectionHeader"><b>The Opportunity</b></h3>
<p>
This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it.</p>
<p>
We are looking for an experienced Senior Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma's customer-facing data products.</p>
<p>
In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery.</p>
<h3 class="jobSectionHeader"><b>
The Role</b></h3>
<p>
At the core of Enigma's product is our data, which makes both data science and delivery systems central to what we build.</p>
<p>
As a Senior ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You'll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems.</p>
<p>
This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems.</p>
<h3 class="jobSectionHeader"><b>
What You'll Do</b></h3>
<ul><li>Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems</li>
<li>Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS</li>
<li>Evaluate and evolve our search technology stack, driving technical design decisions across indexing strategies, retrieval architecture, and system performance tradeoffs</li>
<li>Lead end-to-end work from research design through experimentation, productionization, and customer-facing delivery</li>
<li>Design evaluation frameworks for measuring relevance, precision/recall, ranking quality, and user engagement signals</li>
<li>Improve query understanding via techniques like embedding models, vector search, hybrid retrieval, and query rewriting</li>
<li>Detect and investigate anomalies in search performance, ranking behavior, and data freshness, tracing issues to root cause</li>
<li>Partner closely with Product, Engineering, and client stakeholders to improve search experience and discoverability</li>
<li>Mentor teammates and help raise the bar for experimentation rigor, system design, and operational excellence</li>
</ul><h3 class="jobSectionHeader"><b>What Makes This Role Exciting?</b></h3>
<ul><li><b>Impact: </b>At Enigma, data science and machine learning aren't just used to make product decisions; they are the product. Your work will directly shape how customers find, explore, and trust our data.</li>
<li><b>Technical Challenge</b>: This role spans some of the hardest challenges in search relevance, large-scale retrieval systems, ranking models, APIs, and distributed systems. If you like a technical challenge, this role is for you.</li>
<li><b>Ownership</b>: You'll have meaningful autonomy to shape both research direction and the production systems that power it, including having a strong voice in our tooling and vendor ecosystem.</li>
<li><b>Customer Proximity: </b>Your work will directly influence how sophisticated customers integrate Enigma data into critical workflows and decision-making systems.</li>
</ul><h3 class="jobSectionHeader"><b>Our Ideal Candidate</b></h3>
<ul><li>Brings 5+ years of experience across machine learning, software engineering, data science, or data-intensive product systems</li>
<li>Has strong programming proficiency in Python and experience operating within cloud environments (AWS preferred)</li>
<li>Demonstrated applied, production-level expertise in <b>two or more</b> of the following technical domains: information retrieval, ranking systems, NLP/embedding models, or distributed systems.</li>
<li>Has experience designing, fine-tuning, and operating high-scale backend systems, APIs, or data delivery platforms</li>
<li>Brings strong judgment in ambiguous environments where relevance signals and ground truth are noisy or implicit</li>
<li>Effectively communicates technical concepts and tradeoffs to technical and non-technical audiences</li>
<li>Thrives in highly collaborative environments with strong ownership and fast iteration cycles</li>
<li>Has an advanced degree in a quantitative discipline or equivalent deep industry experience</li>
</ul><h3 class="jobSectionHeader"><b>Bonus Points If You</b></h3>
<ul><li>Have deep experience with our core stack (Typesense, Python, AWS) or similar retrieval infrastructure (Elasticsearch, OpenSearch, FAISS)</li>
<li>Have built customer-facing search or recommendation systems or APIs</li>
<li>Have worked on query understanding, embeddings, LLM-powered retrieval, or hybrid search systems</li>
<li>Have mentored senior engineers or data scientists and raised the technical bar across disciplines</li>
</ul><h3 class="jobSectionHeader"><b>About Us</b></h3>
<p>
At Enigma, we're building the single, most reliable source of data on businesses to power the future of financial services. By engineering better data from hundreds of public and third-party sources, we aim to tell the complete story of every business, so that companies of every size can access the financial services they need to grow and thrive. Our core values &ndash; generosity, curiosity, ingenuity, &amp; drive &ndash; guide everything we do, from how we make our most important product decisions to how we work with and support one another on a daily basis. We're a team of curious, driven individuals with diverse backgrounds and skills, but we're all passionate about engineering deeper understanding through data&mdash;together. If this resonates, we would love to hear from you!</p>
<p>
We are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.</p>
<p><i>
Salary Range: $160,000-$210,000</i></p>
<p><i>
A note on salary ranges: we pride ourselves on paying competitively for our size and industry. Salary is one piece of a total Enigma compensation package that includes additional benefits and opportunities. All of our compensation packages include equity because we believe 100% of Enigma employees should have the option to purchase ownership in the company and benefit from the value we're creating together.</i></p></div>

Senior Machine Learning Engineer, Match Team

Match Group

<div><div><b>Hinge is the dating app designed to be deleted</b></div><div></div><div><br>
In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we&rsquo;re on a mission to inspire intimate connection to create a less lonely world. We&rsquo;re obsessed with understanding our users&rsquo; behaviors to help them find love, and our success is defined by one simple metric&ndash; setting up great dates. With millions of users across the globe, we&rsquo;ve become the most trusted way to find a relationship, for all.</div><div></div><div><b><br>
About the Role</b></div>
<div></div>
<div>Join Hinge as a Senior Machine Learning Engineer, where you'll lead the application of AI and machine learning to effectively mitigate the impact of bad actors, remove policy violating content, and ensure user safety on the platform. Working closely with an expanding Trust &amp; Safety team, you will collaborate with product managers, data scientists, engineers, and analysts to develop impactful AI/ML solutions. In this high-impact position within a small, dynamic team, you'll have the opportunity to play a foundational role in shaping how Hinge utilizes AI and machine learning in various contexts. Your expertise will be instrumental in creating a safer and more meaningful user experience on their journey to find an intimate connection.</div>
<h3 class="jobSectionHeader"><b>Responsibilities</b></h3><ul>
<li>Develop, deploy, and maintain end-to-end machine learning models to identify and mitigate bad actors, remove policy-violating content, and ensure user safety.</li>
<li>Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines.</li>
<li>Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions.</li>
<li>Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations.</li>
<li>Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety.</li>
<li>Stay abreast of new trends and research in AI/ML that can be applied to Trust &amp; Safety initiatives to improve detection, user safety, and stay ahead of potential threats.</li>
</ul><h3 class="jobSectionHeader"><b>What We're Looking For</b></h3><ul>
<li><b>Strong programming skills:</b> Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines</li>
<li><b>Domain expertise:</b> Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus .</li>
<li><b>System design &amp; architecture:</b> Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference.</li>
<li><b>Evaluation frameworks for LLMs:</b> Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features.</li>
<li><b>Cloud and data platform proficiency: </b>The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow is a plus.</li>
<li><b>Data engineering knowledge: </b>Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow.</li>
<li><b>Strategic technical leadership skills: </b>Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives.</li>
<li><b>Collaboration and communication skills:</b> The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.</li>
<li><b>Strong written communication: </b>The ability to communicate complex ideas and technical knowledge through documentation.</li>
</ul><div><b>Prior Experience</b></div>
<ul><li>4+ years of experience, depending on education, as an MLE or data scientist. Previous experience working in Trust &amp; Safety or related fields (e.g., fraud detection, content moderation, compliance) is preferred.</li>
<li>2+ years of experience in applying end-to-end machine learning models, including data collection, model training, deployment, and monitoring in an industry setting</li>
<li>1+ years of experience integrating LLMs in real-world applications with the appropriate baseline metrics and evaluation methodologies.</li>
<li>1+ years of experience utilizing ML infrastructure components such as a feature store, model training environment, model serving environment, observability, workflow orchestrator, etc.</li>
<li>A degree in computer science, engineering, or a related field (or equivalent practical experience).</li>
</ul><div>Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York City. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.</div><div><b>
As a member of our team, you&rsquo;ll enjoy:</b></div><div></div><div><b><br>
401(k) Matching:</b> We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year.</div><div></div><div><b><br>
Professional Growth: </b>Get an annual Learning &amp; Development stipend once you&rsquo;ve been with us for three months. You also get free access to Udemy, an online learning and teaching marketplace with over 6000 courses, starting your first day.</div><div></div><div><b><br>
Parental Leave &amp; Planning:</b> When you become a new parent, you&rsquo;re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents.)</div><div></div><div><b><br>
Fertility Support:</b> You&rsquo;ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide a stipend towards fertility preservation. You and your spouse/domestic partner are both eligible.</div><div></div><div><b><br>
Date Stipend:</b> All Hinge employees receive a $100 monthly stipend for epic dates&ndash; Romantic or otherwise. Hinge Premium is also free for employees and their loved ones.</div><div></div><div><b><br>
ERGs:</b> We have eight Employee Resource Groups (ERGs)&mdash;Asian, Unapologetic, Disability, LGBTQIA+, Raices, Women/Nonbinary, Parents &mdash;that hold regular meetings, host events, and provide dedicated support to the organization &amp; its community.</div><div></div><div><b><br>
At Hinge, our core values are&hellip;</b></div><div></div><div><b><br>
Authenticity:</b> We share, never hide, our words, actions and intentions.</div><div></div><div><b><br>
Courage:</b> We embrace lofty goals and tough challenges.</div><div></div><div><b><br>
Empathy:</b> We deeply consider the perspective of others.</div><div></div><div><b><br>
Diversity inspires innovation</b></div><div></div><div><br>
Hinge is an equal-opportunity employer. We value diversity at our company and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds.</div><div></div><div><b><i><br>
If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please let your Talent Acquisition partner know.<br>
</i></b></div><div></div><br>
<div><i>#Hinge</i></div>
<p>
.</p></div>

Senior Machine Learning Engineer, Trust & Safety

Menarini

<div>Overview:
<p><b>
Senior AI Engineer</b></p><p><b>
Reports to Global Head of Information Technology, Oncology</b></p><p></p><p><b><br>
Opportunity</b></p><p></p><p><br>
Menarini Stemline is seeking a highly motivated and experienced Senior AI/ML Engineer, who will be the technical powerhouse translating our Enterprise Business Architect&rsquo;s strategic roadmap into production-ready intelligence. You won&rsquo;t just be building chatbots; you will be engineering <b>Agentic Workflows</b> and <b>leveraging 3rd party models</b> that accelerate drug development, optimize clinical protocols, and automate complex regulatory filings.</p><p>
You will sit at the intersection of <b>Data Science, Software Engineering, and Biotech value chain</b>, turning massive datasets into actionable therapeutic insights.</p><p>
The successful candidate will be a key contributor in shaping our AI/ML strategy, evaluating and implementing solutions, and demonstrating the value of data-driven decision-making. This role requires a blend of deep technical expertise, strategic thinking, and the ability to collaborate effectively with cross-functional teams.</p>
Responsibilities:
<ul><li><b>Strategic Development:</b> Collaborate with the Menarini Stemline IT leadership team to define and execute the company's AI/ML roadmap. Identify and prioritize high-impact use cases across various business functions, including clinical development, commercialization and enabling functions.</li><li><b>
End-to-End AI Development:</b> Design, develop, and deploy machine learning models (LLMs, Diffusion Models, GNNs) specifically tailored for biotech use cases.</li><li><b>
Agentic Workflow Engineering:</b> Build &quot;AI Agents&quot; capable of navigating complex R&amp;D tasks&mdash;such as searching historic clinical study data libraries or cross-referencing clinical trial data&mdash;to support scientific decision-making.</li><li><b>
MLOps &amp; Pipeline Scalability:</b> Build and maintain robust MLOps pipelines to ensure models are reproducible, versioned, and scalable across our high-performance computing (HPC) environment.</li><li><b>
Architectural Collaboration:</b> Partner with the <b>Principal Business Architect</b> to ensure AI solutions align with the enterprise &quot;Target State&quot; and integrate seamlessly with existing CTMS and ERP systems. Cross-Functional Collaboration: Partner with stakeholders from R&amp;D, Clinical Operations, Regulatory Affairs, and other departments to understand their needs and translate them into AI/data science questions and solutions. Serve as a subject matter expert on AI/ML, providing guidance and training to colleagues.</li><li><b>
Data Engineering for Science:</b> Work with bioinformaticians to curate &quot;AI-ready&quot; datasets from unstructured lab notes, &quot;Omics&quot; data, and Real-World Evidence (RWE).Work closely with IT and data engineering teams to ensure the availability and quality of data required for AI/ML initiatives. Contribute to the development of our data infrastructure and best practices for data governance and management.</li><li><b>
Solution Evaluation and Implementation:</b> Lead the technical evaluation of both internal and external AI/ML solutions. Design, build, and deploy scalable and robust machine learning models on our GCP/Databricks platform. Assess and integrate vendor-provided AI/ML technologies, ensuring they meet our scientific and business requirements.</li><li><b>
Compliance &amp; Validation:</b> Ensure all AI deployments meet stringent <b>GxP</b> requirements and maintain high standards for model explainability and &quot;Human-in-the-loop&quot; safety.</li><li>
Innovation and Research: Stay abreast of the latest advancements in machine learning, artificial intelligence, and data science. Champion a culture of innovation by exploring novel approaches and technologies that can be applied to our business challenges.</li><li>
</li></ul>
Qualifications:
<div>
Education: Master's or Ph.D. in a quantitative field such as Computer Science, Data Science, or a related discipline.</div><div></div><div><br>
Experience: 8 years with 3-5 years of hands-on experience in data science and machine learning, with a proven track record of developing and deploying AI/ML models in a corporate environment.</div><div></div><div><br>
Technical Skills:</div><ul><li>
Expert proficiency in programming languages such as Python or R.</li><li>
Extensive experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch).</li><li>
Strong knowledge of SQL and experience working with relational and non-relational databases.</li><li><b>
Generative AI Expertise:</b> Hands-on experience with <b>RAG (Retrieval-Augmented Generation)</b>, fine-tuning LLMs, and working with vector databases
</li><li>Hands-on experience with cloud computing platforms, preferably Google Cloud platform, Microsoft Azure and Databricks.</li><li>
Solid understanding of software engineering best practices, including version control (Git), testing, and CI/CD.</li></ul><div>
Soft Skills:</div><ul><li>
Excellent problem-solving and analytical skills.</li><li>
Strong communication and interpersonal skills, with the ability to convey complex technical concepts to non-technical audiences.</li><li>
Demonstrated ability to work independently and as part of a collaborative team.</li><li>
A strategic mindset and the ability to think creatively and drive innovation.</li></ul><p><b><i>
Please note: this position is classified as a corporate office position. In accordance with the New York employer convenience rule, Stemline will withhold New York state income taxes for all corporate office employees, regardless of whether these employees work in New York or remotely.</i></b></p><p><br>
</p><p>Base Salary Range of $225,000 - $280,000. Menarini Stemline offers generous compensation and benefits packages, including Short- and Long-Term Incentive Programs, Fidelity 401(k) (with company match), Anthem Premier PPO and HDHP insurance plans, Company paid Basic Life &amp; AD&amp;D insurance and pre-tax FSA/HSA programs.
</p><p>Menarini Stemline is committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.</p><p></p><p><i><br>
Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions.</i></p><p></p><p><b><br>
The Company</b></p><p></p><p><br>
Founded in 1886 in Naples under the name of Farmacia Internazionale, Menarini moved in 1915 to Florence where the Group&rsquo;s headquarters are still located today. High quality therapeutics and diagnostics solutions for patients, ethics as our underlying principle, dedication to innovation and advancement, strong people centricity and environmental sustainability. These five pillars form the foundation of the Menarini Group, an Italian pharmaceutical company with nearly 135 years of history.</p><p><br>
</p><p>The Menarini Group is present in 70 countries and our products are sold in 140 locations around the world. Its companies span from Europe to Asia, to Africa and the Middle East, to Central America and to the United States where with the acquisition of Stemline Therapeutics, a NASDAQ-listed biopharmaceutical company, the company marked its entry into the US oncology market.</p><p></p><p><br>
Thanks to the valuable contribution of around 18,000 employees, every year more than 500 million packs of drugs are produced at the Group's 18 manufacturing sites including a biotech plant for the manufacturing of monoclonal antibodies that also serves external clients distributed across 6 continents.</p><p></p><p><br>
Menarini has made a strong commitment to oncology, investing in a pipeline of five investigational compounds for the treatment of a variety of haematological and solid tumours. The acquisition of Stemline Therapeutics in June 2020, further strengthened Menarini&rsquo;s oncology portfolio, adding both commercial and clinical-stage assets. Tagraxofusp is a novel, first in class targeted therapy for patients with blastic plasmacytoid dendritic cell neoplasm (BPDCN) and to date, the only approved treatment for BPDCN in the U.S. and EU, and the first and only approved CD123-targeted therapy. Tagraxofusp is also being evaluated as both a single agent and in combination, in other CD123+ indications, including acute myeloid leukaemia (AML), chronic myelomonocytic leukaemia (CMML), and myelofibrosis (MF).</p><p><br>
</p><p>Additionally, Menarini received exclusive rights to commercialise Selinexor for the treatment of oncology indications in the European Union and other European countries (including the United Kingdom), Latin America and other key countries. Menarini has signed an exclusive licensing agreement with Karyopharm Therapeutics for the rights to commercialise an innovative therapeutic option in Europe, Latin America, Turkey, Russia, and CIS countries. Selinexor is a first-in-class, oral Selective Inhibitor of Nuclear export compound for the treatment of hematologic cancers and solid tumours. It is already marketed in the US for multiple myeloma and is under development for solid tumour indications. Selinexor is registered in the EU for both early and late lines.</p><p></p><p><br>
Menarini entered into a global licence agreement with Radius Health to complete the development of Elacestrant, an oral SERD in late-stage Phase 3 development for hormone receptor-positive advanced breast cancer. Following a successful phase 3 study, Menarini Stemline received FDA approval in January 2023 under priority review and successfully oversaw a strong launch in February to the US market with the EMA review process concluded positively in September 2023.</p><p><br>
</p><p>It is an exciting time in the company&rsquo;s development and an excellent opportunity for individuals joining us to contribute to building and shaping Menarini Stemline&rsquo;s Oncology business.</p></div>

Senior AI Engineer

Spotify

<div>
 The Music Promotion team is building products that allow creators to promote their work to reach new audiences and create lasting connections with their fans. We&rsquo;re looking for a Machine Learning Engineer to help us build systems that more accurately understand the performance that promotion can have, giving customers actionable insights for building their promotion strategies, whether it&rsquo;s a DIY artist or an industry-facing partner.
 <br/>
 <br/>
 As an ML Engineer, you will help execute on strategies for understanding the factors that play a role in the performance of promoted tracks across the globe. You&rsquo;ll build data-driven solutions, as well as effective online and offline strategies to efficiently iterate and evaluate model approaches. You&rsquo;ll have access to a growing list of datasets, features and ML infrastructure to continually experiment and improve the model-based approach.
 <br/>
 <br/>
 What You'll Do
 <br/>
 <br/>
 <ul>
  <li>
   Contribute to the design, build, evaluation, shipping, and refinement of systems that improve Spotify&rsquo;s promotional performance with hands-on ML development
  </li>
  <li>
   Collaborate with a multidisciplinary team to optimize machine learning models for production use cases, ensuring they are highly efficient, scalable, and consistently meet well-defined success criteria
  </li>
  <li>
   Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures.
  </li>
  <li>
   Work with Data and ML Engineers to support transitioning machine learning models from research and development into production
  </li>
  <li>
   Implement and monitor model success metrics, diagnose issues, and contribute to an on-call schedule to maintain production stability.
   <br/>
   <br/>
  </li>
 </ul>
 Who You Are
 <br/>
 <br/>
 <ul>
  <li>
   You have experience implementing ML systems at scale in Java, Scala, Python or similar languages as well as experience with ML frameworks such as TensorFlow, PyTorch, etc.
  </li>
  <li>
   You have an understanding of how to bring machine learning models from research to production and are comfortable working with innovative, cutting-edge architectures.
  </li>
  <li>
   You have a collaborative mindset, enjoy working closely with research scientists, machine learning engineers, and data engineers to innovate and improve models.
  </li>
  <li>
   You have experience in optimizing machine learning models for production use cases
  </li>
  <li>
   You preferably have experience with data pipeline tools like Apache Beam, Scio, and cloud platforms like GCP
  </li>
  <li>
   You have some exposure to causal ML models, including things like counterfactuals.
  </li>
  <li>
   You are familiar with creating model success metric dashboards, diagnosing production issues, and are willing to take part in an on-call schedule to maintain performance.
   <br/>
   <br/>
  </li>
 </ul>
 Where You'll Be
 <br/>
 <br/>
 We offer you the flexibility to work where you work best! For this role, you can be within the EST time zone as long as we have a work location.
 <br/>
 <br/>
 The United States base range for this position is $170,000 - $212,000 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.
 <br/>
 <br/>
 Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what&rsquo;s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It&rsquo;s in our differences that we will find the power to keep revolutionizing the way the world listens.
 <br/>
 <br/>
 At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we&rsquo;re here to support you in any way we can.
 <br/>
 <br/>
 Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world&rsquo;s most popular audio streaming subscription service.
</div>


Machine Learning Engineer

Meltwater

<div>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 Meltwater, a pioneer of media intelligence and now Outside Insight, gives businesses the information advantage they need to stay ahead. More than 30,000 companies have used Meltwater&rsquo;s media intelligence to stay on top of billions of online conversations and extract relevant insights to strategically manage their brands. Meltwater is dedicated to personal, global service built on the local expertise of 55 offices across six continents. Meltwater is also committed to fostering the data science ecosystem through MEST, a pan-African entrepreneurial program and incubator, and Shack15, a global data science community.
 <br/>
 <br/>
 Our AI team is young, ambitious and focused on innovation.
 <br/>
 <br/>
 With Meltwater, we are more than 2000 people across the globe, so there is a lot going on. We believe in diversity and inclusion, and building teams with a wide variety of backgrounds and perspectives. This approach not only raises the quality of our products for our customers, but makes collaboration along the way much more fun.
 <br/>
 <br/>
 Read our underthehood blog to see which problems our engineers are solving.
 <br/>
 <br/>
 Meltwater&rsquo;s Consumer Intelligence AI Team is looking for a Machine Learning Engineer to help improve the multimodal semantic layer of MIRA, our AI assistant, while also developing innovative new features that power the next generation of applied generative AI in the Consumer Intelligence industry. This includes building agentic capabilities that allow MIRA to reason across data sources, orchestrate multi-agent/multi-step workflows, and generate complex, use-case driven reports for customers.
 <br/>
 <br/>
 We are looking for someone with a creative, proactive, collaborative, and innovation focused mindset. You will work alongside a team of passionate machine learning engineers driven by enthusiasm for adopting new technologies and excitement about making the difference for customers using applied AI.
 <br/>
 <br/>
 As a Machine Learning Engineer at Meltwater, you will own machine learning powered features from idea to production, working on systems that operate at massive scale. You should be comfortable with experimentation, collaboration, and real-world impact.
 <br/>
 <br/>
 <strong>
  What we're looking for:
  <br/>
  <br/>
 </strong>
 This role is ideal for candidates with a strong foundation in machine learning, data science, or applied research who enjoy experimentation and model-driven problem solving and who want to translate their work into real-world, production systems at scale. You are excited to grow your software engineering and production skills over time, while bringing strong foundations in experimentation, modeling, evaluation, and applied machine learning.
 <br/>
 <br/>
 Our team is organized over 3 objectives : innovation, research and production.
 <br/>
 <br/>
 <strong>
  Innovation:
 </strong>
 We leverage our AI expertise to constantly imagine new business oriented features to enhance our products.
 <br/>
 <br/>
 <strong>
  Research:
 </strong>
 To implement our algorithms, we need to stay up-to-date to the latest breakthroughs over the Machine Learning world as well as the latest frameworks.
 <br/>
 <br/>
 <strong>
  Production
 </strong>
 : We make a point of designing and developing our algorithms with production-grade best practices. Scalability is our goal. The models and systems that we develop are running over billions of documents (text or image) per day.
 <br/>
 <br/>
 <strong>
  Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Drive the development of industrial ML projects from ideation to deployment, contributing across early prototyping, research, evaluation, and progressively to production, scalability, and monitoring with support from the team.
  </li>
  <li>
   Collaborate closely with product teams in their domains, building domain expertise, and leveraging ML to solve critical business problems
  </li>
  <li>
   Keep up-to-date with the latest advancements in machine learning to stay current on emerging techniques to solve novel problems
  </li>
  <li>
   Design, run, and iterate on machine learning experiments to improve model quality and product impact
  </li>
  <li>
   Develop features, online and offline evaluation metrics, and validation strategies for large-scale ML systems
  </li>
  <li>
   Analyze model errors and failure modes to understand limitations, biases, and opportunities for improvement.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You'll Do:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Drive the development of new industrial level projects from ideation to deployment. This includes deep expertise in areas such as early ideation &amp; prototyping, research, infrastructure, scalability, monitoring, and evaluation of AI systems.
  </li>
  <li>
   Collaborate closely with product teams in their domains, building domain expertise, and leveraging ML to solve critical business problems
  </li>
  <li>
   Keep up-to-date with the latest advancements in machine learning to stay current on emerging techniques to solve novel problems
  </li>
  <li>
   You&rsquo;ll write efficient, well-tested and design code, build clean systems to empower MIRA with new advanced generative AI capabilities
  </li>
  <li>
   Demonstrable experience with the full lifecycle of machine learning models - from development to deployment and monitoring
  </li>
  <li>
   Experience building industry-scale user-facing ML/AI/Agentic applications
  </li>
  <li>
   Experience with MLOps and DevOps principles and technologies (e.g. CI/CD, Terraform, Containerization, Kubernetes)
  </li>
  <li>
   Experience with Information Retrieval systems in a production environment (Elasticsearch, Quickwit, Vespa, &hellip;) is a plus
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You'll Bring:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   2+ years experience applying machine learning techniques through academic, professional, or personal projects, ideally with exposure to experimentation, modeling, or applied research.
  </li>
  <li>
   Solid foundation in machine learning concepts such as feature engineering, model selection, training, validation, and error analysis
  </li>
  <li>
   Ability to write clear, well-structured code, with motivation to grow software engineering skills and contribute to production ML systems
  </li>
  <li>
   Experience reasoning about metrics, tradeoffs, experiments, and uncertainty in applied ML problems
  </li>
  <li>
   You are comfortable learning new tools, concepts, or techniques as needed, and enjoy expanding beyond your initial area of strength.
  </li>
  <li>
   Advanced knowledge in a least one programming language (Python or other e.g. Rust, Scala, Java)
  </li>
  <li>
   Passion for AI (in particular Generative AI), with a constant drive to stay updated and ahead of the curve
  </li>
  <li>
   You are a team-player, self-learner and autonomous
  </li>
  <li>
   MS, PhD, or equivalent practical experience in machine learning, data science, or a related technical field
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Offer:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You will work with a team of passionate people who are always willing to help and learn from others
  </li>
  <li>
   You will have the opportunity to apply the most recent literature to concrete AI projects with a real impact on business
  </li>
  <li>
   As a growing company, we combine a startup mindset with the resources necessary to commit to exciting new initiatives. At Meltwater, everyone has an opportunity to make a difference
  </li>
  <li>
   Enjoy flexible paid time off that allows you to have an enhanced work-life balance.
  </li>
  <li>
   Excellent medical, dental, and vision options
  </li>
  <li>
   401(k) matching, life insurance, commuter benefits, and parental leave plans
  </li>
  <li>
   Complimentary CalmApp subscription for you and your loved ones, because mental wellness matters.
  </li>
  <li>
   Energetic work environment with a hybrid work style, providing the balance you need.
  </li>
  <li>
   Thrive within our inclusive community and seize ongoing professional development opportunities to elevate your career.
  </li>
  <li>
   Total compensation range for this position: $150-200 per year (Depending on insurance)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Where You'll Work:
  <br/>
  <br/>
 </strong>
 New York
 <br/>
 <br/>
 <strong>
  When you'll join:
  <br/>
  <br/>
 </strong>
 May/June 2026
 <br/>
 <br/>
 <strong>
  Our Story
  <br/>
  <br/>
 </strong>
 At Meltwater, we believe that when you have the right people in the right environment, great things happen.
 <br/>
 <br/>
 Our best-in-class technology empowers our
 <strong>
  27,000 customers
 </strong>
 around the world to make better business decisions through data. But we can&rsquo;t do that without our global team of developers, innovators, problem-solvers, and high-performers who embrace challenges and find new solutions for our customers.
 <br/>
 <br/>
 Our award-winning global culture drives everything we do and creates an environment where our employees can make an impact, learn every day, feel a sense of belonging, and celebrate each other&rsquo;s successes along the way.
 <br/>
 <br/>
 We are innovators at the core who see the potential in people, ideas and technologies. Together, we challenge ourselves to go big, be bold, and build best-in-class solutions for our customers.
 <br/>
 <br/>
 We&rsquo;re proud of our diverse team of
 <strong>
  2,200+ employees
 </strong>
 in
 <strong>
  50 locations
 </strong>
 across
 <strong>
  25 countries
 </strong>
 around the world. No matter where you are, you&rsquo;ll work with people who care about your success and get the support you need to unlock new heights in your career.
 <br/>
 <br/>
 <strong>
  We are Meltwater. Inspired by innovation, powered by people.
  <br/>
  <br/>
 </strong>
 <strong>
  Our Team
  <br/>
  <br/>
 </strong>
 Our AI team is young, ambitious and focused on innovation. With Meltwater, we are more than 2000 people across the globe, so there is a lot going on. We believe in diversity and inclusion, and building teams with a wide variety of backgrounds and perspectives. This approach not only raises the quality of our products for our customers, but makes collaboration along the way much more fun.
 <br/>
 <br/>
 Read our under-the-hood blog to see which problems our engineers are solving.
 <br/>
 <br/>
 <em>
  Equal Employment Opportunity Statement
  <br/>
  <br/>
 </em>
 <em>
  Meltwater is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind: At Meltwater, we are dedicated to fostering an inclusive and diverse workplace where every employee feels valued, respected, and empowered. We are committed to the principle of equal employment opportunity and strive to provide a work environment that is free from discrimination and harassment.
  <br/>
  <br/>
 </em>
 <em>
  All employment decisions at Meltwater are made based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, veteran status, or any other status protected by the applicable laws and regulations.
  <br/>
  <br/>
 </em>
 <em>
  Meltwater does not tolerate discrimination or harassment of any kind, and we actively promote a culture of respect, fairness, and inclusivity. We encourage applicants of all backgrounds, experiences, and abilities to apply and join us in our mission to drive innovation and make a positive impact in the world.
  <br/>
  <br/>
  We may use AI to assist in aspects of our hiring process, such as reviewing candidate information and supporting evaluation activities. These tools are used only to assist our team through increased efficiencies. Every output continues to be reviewed by humans, and all hiring decisions are made by humans. We remain committed to evaluating candidates fairly, consistently, and in compliance with all applicable laws
 </em>
</div>


Explore 819+ Senior lead machine learning engineer in New York this April. Find roles across top companies and apply now to boost your career.

819 senior lead machine learning engineer jobs In New York

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