Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The CreativeX RAPID(Real-time Ad Personalization &amp; Insights Development) team is seeking passionate and talented MLE to join us. CreativeX is on a mission to enable brands of all sizes and categories to create, serve, measure, and optimize creative content with ease. Our team is responsible for tailoring the visual experience of ads to each context in real-time, leveraging nouvelle technologies such as latent diffusion models, large language models (LLM), reinforced learning (RL), computer vision, and related methods. 
 
Our mission is to provide engaging, dynamically optimized creatives with low latencies both on and off Amazon for self-service brand advertisers. We automate the customization of product creatives with real-time catalog data while providing advertisers with the flexibility to customize their creatives according to their preferences. 
 
Key job responsibilities 
<ul><li>Quickly acquire knowledge of nouvelle technologies in Generative AI to solve complex problems in the Dynamic Creative Optimization (DCO) domain.</li></ul>
 
<ul><li>Investigate design approaches, prototype new technologies, and evaluate their technical feasibility, such as Auto ML, real-time ML serving systems.</li></ul> 
<ul><li>Collaborate with scientists to design and build data pipelines for processing massive datasets and scaling machine learning models.</li></ul> 
<ul><li>Develop and maintain platforms for developing, evaluating, and deploying machine learning models for real-world applications.</li></ul></div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience programming with at least one software programming language</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, NY, New York - 158,100.00 - 213,800.00 USD annually</div>

Software Development Engineer, CreativeX

Capital One

<div>Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), 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.
What you&rsquo;ll do in the role:
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:<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>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 6 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 2 years of experience building, scaling, and optimizing ML systems</li></ul>
Preferred Qualifications:<ul><li>
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow</li><li>
2+ years of experience developing performant, resilient, and maintainable code</li><li>
2+ years of experience with data gathering and preparation for ML models</li><li>
2+ years of people leader experience</li><li>
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li></ul>
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).
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.
McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer 
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.
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.
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.
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.
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.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
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.
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).</div>

Lead Machine Learning Engineer

<div>Senior Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), 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.
What you&rsquo;ll do in the role:
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:<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>
Basic Qualifications:<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>
Preferred Qualifications:<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>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 
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.
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.
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.
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.
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.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
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.
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).</div>

Senior Lead Machine Learning Engineer

Information Technology Senior Management Forum

<div><div>Posted Date
4/10/2026
</div><div>Description
<div>Senior Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), 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.
What you&rsquo;ll do in the role:
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:<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>
Basic Qualifications:<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>
Preferred Qualifications:<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>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 
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.
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.
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.
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.
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.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
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.
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).
Senior Lead Machine Learning Engineer
As a Capital One Machine Learning Engineer (MLE), 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.
What you&rsquo;ll do in the role:
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:<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>
Basic Qualifications:<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>
Preferred Qualifications:<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>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.
Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 
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.
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.
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.
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.
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.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
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.
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).</div>
</div><div>Salary
229,900.00 - 262,400.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Match Group

<div><div>Hinge is the dating app designed to be deleted</div><div></div><div> 
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> 
About the Role</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">Responsibilities</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">What We're Looking For</h3><ul>
<li>Strong programming skills: 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>Domain expertise: 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>System design &amp; architecture: Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference.</li>
<li>Evaluation frameworks for LLMs: Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features.</li>
<li>Cloud and data platform proficiency: 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>Data engineering knowledge: 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>Strategic technical leadership skills: Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives.</li>
<li>Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.</li>
<li>Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation.</li>
</ul><div>Prior Experience</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>
As a member of our team, you&rsquo;ll enjoy:</div><div></div><div> 
401(k) Matching: 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> 
Professional Growth: 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> 
Parental Leave &amp; Planning: 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> 
Fertility Support: 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> 
Date Stipend: 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> 
ERGs: 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> 
At Hinge, our core values are&hellip;</div><div></div><div> 
Authenticity: We share, never hide, our words, actions and intentions.</div><div></div><div> 
Courage: We embrace lofty goals and tough challenges.</div><div></div><div> 
Empathy: We deeply consider the perspective of others.</div><div></div><div> 
Diversity inspires innovation</div><div></div><div> 
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> 
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. 
</div><div></div> 
<div>#Hinge</div>

.</div>

Senior Machine Learning Engineer, Trust & Safety

Walmart

<div><h2 class="jobSectionHeader">Position Summary...</h2><h2 class="jobSectionHeader">
What you'll do...</h2>
Walmart Marketplace 
 
Walmart Marketplace is a key part of e-commerce at Walmart. It is a gateway for Third-Party Sellers to manage their operations, such as onboarding, catalogs, order fulfillment, global opportunities, and return &amp; refund management. We are responsible for providing the best in-class marketplace experience for our sellers and customers through the design, development, and operations of highly scalable systems. We interact with multiple teams within the company to develop scalable, robust technical solutions. The data scientist role will be part of the data science team and will play a key role working along with others within the Marketplace engineering organization, product managers and business stakeholders to build Machine Learning products. 
 
More about Marketplace: https://marketplace.walmart.com/
 
 
What you'll do: As a full stack Staff Data Scientist for Walmart, you will be responsible for building scalable end-to-end data science solutions for our data products.
<ul><li>Own the MLOps lifecycle, from data monitoring to refactoring data science code to building robust model monitoring workflows for model lifecycle management</li><li>
Can develop and maintain scalable MLOps infrastructure, such as building Kafka pipeline for unified logging and monitoring across multiple projects.</li><li>
Apply SRE (Site Reliability Engineering) principles for ML workloads, optimizing cloud deployments, monitoring performance and troubleshooting application latency or operational issues.</li><li>
Lead code quality and engineering best practices by conducing code reviews and mentoring junior MLEs.</li><li>
Can provide high-level architectural project guidance, break down complex tasks, and help resolve project challenges for the team.</li><li>
Build continuous, distributed and scalable training pipeline, inference pipeline and performance monitoring pipeline to be used across several Marketplace initiatives.</li><li>
Enhance data feedback/annotation workflows to improve efficiency of our labeling team</li><li>
Demonstrate strong thought-leadership and consult with product and business stakeholders to build, scale and deploy holistic machine learning solutions after successful prototyping.</li><li>
Collaborate cross-functionally with stakeholders to align AI solutions with Walmart&rsquo;s business objectives.</li><li>
Build and deploy end-to-end models, balancing accuracy, computational efficiency, and business impact.</li></ul> 
 
 
What you'll bring:
<ul><li>Very good knowledge of the foundations of machine learning and statistics</li><li>
Experience in machine learning, supervised and unsupervised and deep learning.</li><li>
Experience in analyzing the complex problems and translate it into data science algorithms</li><li>
Experience with big data analytics - identifying trends, patterns, and outliers in large volumes of data
</li><li>Strong Experience in Python with excellent knowledge of Data Structures</li><li>
Strong Experience with big data platforms &ndash; Hadoop (Hive, Pig, Map Reduce, Scala, Spark)
</li><li>Hands on experience with Git</li><li>
Experience with SQL and relational databases, data warehouse</li></ul> 
 
 
About Walmart Global Tech 
Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That&rsquo;s what we do at Walmart Global Tech. We&rsquo;re a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world&rsquo;s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered. We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail. Walmart&rsquo;s culture is a competitive advantage, and it&rsquo;s fostered by being together. Working together in person allows us to collaborate, align quickly and innovate with greater speed. We use our campuses to create purposeful connection rooted in deepening understanding and investing in the development of our associates. 
Our hubs: Walmart is a global company with offices across the United States and around the world. Our global headquarters is in Bentonville, Arkansas, with primary hubs in the San Francisco Bay area and New York/New Jersey.
 
 
Benefits: 
Benefits: Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and much more. 
 
Equal Opportunity Employer: 
Walmart, Inc. is an Equal Opportunity Employer &ndash; By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing unique styles, experiences, identities, ideas, and opinions &ndash; while being inclusive of all people. 
 
The above information has been designed to indicate the general nature and level of work performed in the role. It is not designed to contain or be interpreted as a comprehensive inventory of all responsibilities and qualifications required of employees assigned to this job. The full Job Description can be made available as part of the hiring process. 
 At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see https://one.walmart.com/notices. Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.
 
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
 
For information about benefits and eligibility, see One.Walmart.
 
The annual salary range for this position is $110,000.00 - $220,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
 
<ul><li>Stock</li></ul>
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&lrm;<h2 class="jobSectionHeader">
Minimum Qualifications...</h2>
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field<h2 class="jobSectionHeader">
Preferred Qualifications...</h2>
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart&rsquo;s accessibility standards and guidelines for supporting an inclusive culture.<h2 class="jobSectionHeader">
Primary Location...</h2>
2501 Se J St, Ste A, Bentonville, AR 72716-3724, United States of America
Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.</div>

(USA) Staff, Data Scientist

Cohere

<div>
 
 Who are we?
 
 
 
 Our mission is to scale intelligence to serve humanity. We&rsquo;re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what&rsquo;s best for our customers.
 
 
 Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
 
 
 Join us on our mission and shape the future!
 
 
 We are expanding our Talent Team and are looking for a creative, high-performing Technical Recruiter eager to take on a new challenge.
 
 
 In this role, you will own full cycle recruitment efforts across our tech teams, including Research, Applied ML, and Engineering.
 
 
 
 As a Talent Partner At Cohere, You Will
 
 
 
 <ul>
 <li>
 Own a world class full lifecycle recruitment process, attracting and recruiting top talent for a large volume of senior level roles across engineering teams.
 </li>
 <li>
 Partner with hiring managers and org leaders on effective recruiting strategies. Influence where necessary.
 </li>
 <li>
 Manage recruiting funnels in Ashby, with diligence.
 </li>
 <li>
 Proactively source and recruit top talent.
 </li>
 <li>
 Take initiative, introducing talent projects in an effort to optimize efficiencies and take ownership of these projects.
 
 
 </li>
 </ul>
 
 This career opportunity may be a good match for you if you have:
 
 
 
 <ul>
 <li>
 7+ years of full-cycle recruiting experience at high growth technology companies with a focus on delivering top talent for Research, MLE and Engineering teams.
 </li>
 <li>
 Experience managing a high volume senior level desk at a hyper growth startup/scale-up.
 </li>
 <li>
 Creative problem solving skills &amp; thrive under pressure.
 </li>
 <li>
 Strong ability to excel in rapidly evolving ambiguous environments.
 </li>
 <li>
 You are a natural entrepreneur, an influencer, and enjoy working cross-functionally.
 
 
 </li>
 </ul>
 If some of the above doesn&rsquo;t line up perfectly with your experience, we still encourage you to apply!
 
 
 We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 
 Full-Time Employees At Cohere Enjoy These Perks
 
 
 
 🤝 An open and inclusive culture and work environment
 
 
 🧑&zwj;💻 Work closely with a team on the cutting edge of AI research
 
 
 🍽 Weekly lunch stipend, in-office lunches &amp; snacks
 
 
 🦷 Full health and dental benefits, including a separate budget to take care of your mental health
 
 
 🐣 100% Parental Leave top-up for up to 6 months
 
 
 🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
 
 
 🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
 
 
 ✈️ 6 weeks of vacation (30 working days!)
</div>

Talent Acquisition Partner - Tech Recruiter

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