senior machine learning engineer

be group

<div><div>We are assisting our client in hiring for a Senior Machine Learning Engineer.</div>
<div>Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps financial institutions improve collections performance, deliver a better consumer experience, reduce operating costs, anticipate delinquencies, and make more informed credit decisions.</div>
<p>This is a hybrid position based in Malvern, Pennsylvania. Candidates should be local to the Greater Philadelphia region and able to work onsite several days a week.</p>
<p>As part of a significant investment in Data &amp; AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role is focused on building the predictive intelligence that becomes part of the company's core SaaS platform.</p>
<p>This is a highly hands-on engineering opportunity for someone who enjoys solving real business problems with machine learning. You'll design, build, deploy, and continuously improve production models that help financial institutions better predict customer behavior, prioritize collections strategies, and improve lending outcomes.</p>
<p>Working alongside Product, Engineering, Data, and business leaders, you'll help transform large volumes of structured data into intelligent software capabilities that customers use every day. If you enjoy owning the entire machine learning lifecycle&mdash;from feature engineering and model development through deployment, monitoring, and optimization&mdash;this is an opportunity to make a measurable impact.</p>
<h3 class="jobSectionHeader"><b>What We're Looking For</b></h3>
<ul><li>Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.</li>
<li>3+ years of experience designing, developing, and deploying production machine learning solutions.</li>
<li>Strong Python and SQL development skills.</li>
<li>Experience building predictive models using structured data.</li>
<li>Experience with feature engineering, model evaluation, deployment, and ongoing model monitoring.</li>
<li>Experience working with cloud-based data platforms and modern machine learning frameworks.</li>
<li>Familiarity with Azure, Databricks, MLflow, MLOps, or similar technologies.</li>
<li>Experience collaborating with engineering, product, and business teams to deliver production-ready AI solutions.</li>
</ul><h3 class="jobSectionHeader"><b>Preferred Experience</b></h3>
<ul><li>Financial services, banking, lending, collections, credit risk, or fintech.</li>
<li>Building scalable data pipelines and production machine learning systems.</li>
<li>AI-assisted software development tools and modern engineering practices.</li>
<li>Passion for solving complex business problems through data and machine learning.</li></ul></div>

Senior Machine Learning Engineer

Arrow Electronics

<div>
 <strong>
  Position
  <br/>
  <br/>
 </strong>
 Data Scientist / Senior Machine Learning Engineer
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 <strong>
  Job Description
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 <strong>
  Position Overview:
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 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
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  Key Responsibilities
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 </strong>
 <ul>
  <li>
   Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
  </li>
  <li>
   Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
  </li>
  <li>
   Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
  </li>
  <li>
   Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
  </li>
  <li>
   Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
  </li>
  <li>
   Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
  </li>
  <li>
   Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
   <br/>
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  </li>
 </ul>
 <strong>
  Qualifications
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  <br/>
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 <ul>
  <li>
   Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
  </li>
  <li>
   Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
  </li>
  <li>
   Strong knowledge of machine learning frameworks and libraries.
  </li>
  <li>
   Expertise in data preprocessing, feature engineering, and model selection.
  </li>
  <li>
   Familiarity with large language models and AI agent design.
  </li>
  <li>
   Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
  </li>
  <li>
   Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
  </li>
  <li>
   Experience with vectorized databases and unstructured search engines is a plus.
  </li>
  <li>
   A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
  </li>
  <li>
   Publications or contributions to open-source projects are a plus.
   <br/>
   <br/>
  </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
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  Location:
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 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
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  Time Type
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 Full time
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 Information Technology
</div>


Data Scientist / Senior Machine Learning Engineer

Nyla Technology Solutions

Job Description
<br><br>
ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED
<br><br>
Ready to push the boundaries of natural language processing and AI? In this role, you will be at the forefront of automated language processing, tackling complex natural language data from both spoken and written origins. You won't just run off-the-shelf models—you’ll architect autonomous tokenization pipelines, build automated part-of-speech annotation solutions, and rigorously score and benchmark model performance against human-annotated baselines. If you thrive on pushing the boundaries of NLP, fine-tuning machine learning models, and bringing cutting-edge AI/LLM capabilities to high-stakes missions, you’ll fit right in with Team Nyla.
<br><br>
The annual base salary range for this role is $152,000-$180,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
<br><br>
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<br>Required Skills
<br><br>
<b>Python Expertise:</b> Advanced, production-level proficiency in Python for data manipulation, algorithmic modeling, and NLP tool development.
<br><br>
<b>Natural Language Processing (NLP):</b> Extensive hands-on experience designing and deploying core NLP workflows, including tokenization, text normalization, and parts-of-speech (POS) tagging.
<br><br>
<b>Model Evaluation & Scoring:</b> Demonstrated track record of benchmarking machine learning/NLP models, performing error analysis, and measuring accuracy against human-annotated datasets.
<br><br>
<b>Multi-Modal Language Processing:</b> Practical experience processing diverse natural language datasets originating from both spoken (transcribed) and written sources.
<br><br>
<b>Education:</b> Bachelor’s Degree in Data Science, Computer Science, Computational Linguistics, Mathematics, or a related technical discipline, PLUS 7+ years of professional experience in data science, NLP, or software engineering OR Master’s Degree in a related field, PLUS 5+ years of relevant professional experience OR High School Diploma / GED, PLUS 11+ years of specialized technical experience in lieu of a degree.
<br><br>
,
<br>Desired Skills
<br><br>
<b>AI & Large Language Models (LLMs):</b> Hands-on experience testing, fine-tuning, or integrating modern LLMs and generative AI frameworks into production analytical pipelines.
<br><b>Machine Learning & Frameworks:</b> Familiarity with modern ML libraries and deep learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face, spaCy, NLTK).
<br><b>MDLA & Domain Experience:</b> Prior exposure to Massively Distributed Language Processing Frameworks (MDLA) or specialized language processing architectures.
<br><b>AI Testing & Evaluation:</b> Practical experience constructing evaluation testbeds and testing strategies for emerging AI/ML techniques.
<br>,
<br>About Nyla Technology Solutions
<br><br>
Nyla Technology Solutions delivers exceptional Artificial Intelligence (AI), Data Science, and Software Engineering services for the U.S. Government. Nyla embraces a forward-thinking and bold approach at every turn, earning us a solid reputation of technical trendsetters within the industry. We have a passion for developing solutions that have a quick and immediate impact on mission. Headquartered in Columbia, Maryland, our customers love how we tackle their most challenging problems and get things done.
<br><br>
If you have the unique experience and expertise we are seeking, along with the desire and determination to invest your time and energy as a part of Nyla’s team,
<br><br>
Taking Care of All of You
<br>Nyla provides a top-of-market compensation and benefits package. And through our unique Nyla FLEX program, we custom tailor these benefits to best fit your lifestyle.
<br><br>
The Nyla FLEX benefit program is designed to offer you flexibility in the 3 biggest areas of your life: your pay, your leave, and your schedule.
<br><br>
PAY - Nyla starts with 4 weeks of Annual Leave plus 11 holidays and an additional day of Annual Leave for each year you’re at the company. You have the flexibility to cash out your annual leave hours, opt out of other Nyla benefits, and/or arrange for additional hours on contract* (over 40 hrs/week). There’s even an option to earn 1.3 times your hourly rate once you work over 1880 hours on contract!
<br><br>
LEAVE - Want to spend more time with the family? Want more time to travel the world? You can BUY additional annual leave for a total of 6 weeks of annual leave. That’s up to 240 hours of leave plus 11 holidays! That’s not even including paid anniversary leave!
<br><br>
SCHEDULE - Does the traditional 40-hour workweek no longer fit your lifestyle? With Nyla FLEX, you have the freedom to scale down to 30-32 hours while still enjoying the top-notch Nyla benefits you know and love. It's flexibility that works for you without compromising the perks!
<br><br>
WHAT ABOUT OTHER BENEFITS? Nyla’s health care (medical, dental, and vision) is 100% covered by the company. We provide 10% 401k matching - with full vesting day 1! Our Professional Development offers $5,000 per year to be used towards fees, tuition, or time off for your continued growth. We even have a student loan repayment program and we provide 8 hours of volunteering annually so you can support your community, making your world a better place.
<br><br>
To learn more about Nyla's culture and our exceptional benefit packages click here.
<br>Nyla is an equal opportunity employer.

Uber

<div><b>About the Role</b>
<br>
<br>
Uber Freight Marketplace is building the next generation of logistics technology by leveraging Uber's proven marketplace playbook to freight. As part of a small, high-impact team, you'll help bring expertise from Uber's mobility and delivery marketplaces into a rapidly evolving industry, developing pricing, matching, recommendation, and optimization systems that will disrupt the freight industry ($1T TAM). Uber Freight is at a very early stage, with just 0.4% of the pie now, and it's a rare opportunity to solve challenging marketplace problems with AI/ML and marketplace optimization while shaping how the freight industry transforms.
<br>
<br>
We are looking for a highly motivated Machine Learning Engineer to join Uber's Marketplace team to modernize the Uber Freight marketplace team. It is a fascinating area with challenges in predictive modeling, causal inference, constrained optimization, reinforcement learning, marketplace design, etc. The business is about to elevate and this role has a huge growing opportunity.
<br>
<br>
<b>What You'll Do</b>
<br>
<br>
This role requires end to end ownership for the ML models in UF marketplace (cost prediction, booking probability, demand elasticity, etc.). While your job is mostly about model development, you will work with backend engineers together to put them in production and make sure they work as expected.
<br>
<br>
<b>Basic Qualifications</b>
<ul><li>4+ years of experience developing ML models to solve business problem.
</li><li>Bachelor's degree in Computer Science, Computer Engineering, or related fields.
</li><li>Familiar with modern AI/ML frameworks (e.g., PyTorch).
</li></ul><b>Preferred Qualifications</b>
<ul><li>Product experience will be a big plus for this role. Adaptive development of ML models to the business context is critical.
</li><li>Previous experience with state-of-the-art marketplace technology is preferred.
</li>Experience with causal inference and constrained optimization<br>
<li>
</li></ul><br>
<br>
For Chicago, IL-based roles: The base salary range for this role is USD $182,000 per year - USD $202,000 per year.<br>
<br>
For New York City, NY-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.<br>
<br>
For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.<br>
<br>
For Seattle, WA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.<br>
<br>
For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.<br>
<br>
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.<br>
<br>
<b>Ready to Ride?</b><br>
<br>
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.<br>
<br>
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
<br>
<br>
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.<br>
<br>
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.</div>

The Hartford

<div><h2 class="jobSectionHeader"><b>Job Details</b></h2>
<div><div><div>Location:</div>
<div>Hartford, CT</div>
</div><div><div>Category:</div><div>
Data &amp; Analytics</div>
</div><div><div>Employment Type:</div>
<div>Full time
</div></div><div><div>Job Ref:</div><div>
R2626256-168</div>
</div></div><p></p><div><div>Sr Data Engineer - GE07BE<p>
We&rsquo;re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals &ndash; and to help others accomplish theirs, too. Join our team as we help shape the future.<br>
</p><p></p><div><p>The Hartford is seeking a Senior AI Machine Learning Engineer within Employee Benefits Applied AI and Analytics (EB AIA) to help build, deploy, and sustain enterprise-scale predictive and applied AI solutions across pricing, underwriting, sales related EB business workflows. As a Senior AI/ML engineer you will manage and modernize the existing predictive model portfolio while helping the team expand into generative AI, agentic AI and other applied AI capabilities.</p></div><div><p>
The role is intended for a hands-on technical lead who can execute approved solution designs, deploy production-ready AI and ML components, operate reliable model pipelines, and guide junior engineers. The person should be able to translate architecture and design direction into working, governed, and production assets with minimal supervision.</p></div><div><p><b>
Team Description</b></p></div><div><p>
The Employee Benefits Applied AI and Analytics team provides insight, automation, and augmentation across the policy lifecycle for Employee Benefits customers and internal business stakeholders. EB AIA supports a portfolio that spans sales, pricing, underwriting, policy installation, renewal, service, and operational workflows.</p></div><div><p>
In addition to the existing portfolio of Predictive AI assets, the team is scaling an end-to-end AI-driven reimagination of EB underwriting and service organizations. The team partners closely with enterprise platform enablement team to apply consistent architecture and engineering practices while tailoring solutions for accuracy, transparency, scalability, and business usability.</p></div><div><p><b>
Primary Responsibilities</b></p></div><div><ul><li>Lead day-to-day engineering execution for the EB predictive model portfolio, including pricing and underwriting models, scoring pipelines, model refreshes, monitoring, data validations, and production support.</li></ul></div><div><ul><li>Build, deploy, and maintain AI/ML components and data pipelines that support applied AI use cases across pricing, underwriting, sales, service, renewal, and policy lifecycle workflows.</li></ul></div><div><ul><li>Implement approved solution designs from senior Applied AI Engineers, Architects, and Data Scientists; translate design patterns into tested, reliable production code and workflows.</li></ul></div><div><ul><li>Support the initial build-out of generative AI and agentic AI solutions, including prompt orchestration, retrieval-augmented generation patterns, evaluation workflows, guardrails, and integration with existing EB data and application ecosystems.</li></ul></div><div><ul><li>Develop and operate batch and near-real-time data/AI pipelines for model training, feature generation, inference, post-processing, business rules integration, and downstream consumption.</li></ul></div><div><ul><li>Deploy and sustain production AI services, jobs, APIs, and workflows in AWS and GCP environments using approved CI/CD, testing, observability, security, and operational practices.</li></ul></div><div><ul><li>Own implementation quality for assigned components, including code reviews, unit/integration testing, documentation, runbooks, production readiness checks, and incident response support.</li></ul></div><div><ul><li>Guide and mentor junior engineers by breaking down technical work, reviewing code, explaining model/data pipeline patterns, and ensuring consistent engineering practices.</li></ul></div><div><ul><li>Partner with Data Scientists, Data Engineers, Asset Owners, Underwriting, Pricing stakeholders to understand requirements, validate outputs, resolve data issues, and ensure model solutions fit business workflows.</li></ul></div><div><ul><li>Maintain model and pipeline governance artifacts, including lineage, model inputs/outputs, monitoring metrics, validation evidence, operational controls, and handoff documentation.</li></ul></div><div><ul><li>Identify risks, bottlenecks, and operational gaps in deployed AI/ML solutions and recommend practical improvements under the guidance of senior technical leadership.</li></ul></div><div><p><b>
Minimum</b><b> </b><b>Requirements</b></p></div><div><ul><li> Bachelor&rsquo;s degree in related field or 6+ years of equivalent experience in software engineering, data engineering, ML/DevOps engineering, applied AI engineering, or closely related technical roles.</li></ul></div><div><ul><li>Master's degree in computer science, engineering, information technology, MIS, data science, or related discipline preferred.</li></ul></div><div><ul><li>Strong hands-on expertise in Python, SQL, SDLC practices, Git-based development, automated testing, and production-grade code delivery.</li></ul></div><div><ul><li>Experience deploying and operating data, AI, or ML workloads in AWS and GCP, including cloud storage, managed compute, orchestration, IAM-aware access patterns, logging, and monitoring.</li></ul></div><div><ul><li>Experience with ML engineering concepts such as feature pipelines, model training workflows, batch scoring, inference services, model monitoring, drift detection, validation, retraining, and production support.</li></ul></div><div><ul><li>Ability to work within defined architecture, enterprise security standards, data governance expectations, coding standards, and operational controls.</li></ul></div><div><ul><li>Ability to lead implementation work, guide junior engineers, communicate tradeoffs, and manage multiple model/pipeline deliverables with limited day-to-day direction.</li></ul></div><div><p><b>
Preferred Experience</b></p></div><div><ul><li>Experience in insurance, employee benefits, pricing, underwriting, risk selection, sales enablement, or policy lifecycle analytics.</li></ul></div><div><ul><li>Experience supporting predictive model portfolios that require periodic refreshes, performance tracking, business validation, and governed production deployment.</li></ul></div><div><ul><li>Experience with generative AI or agentic AI implementation patterns, including RAG, prompt evaluation, LLM application integration, AI safety controls, human-in-the-loop workflows, and model output validation.</li></ul></div><div><ul><li>Experience with orchestration and workflow tools such as Airflow, Cloud Composer, Step Functions, Vertex AI Pipelines, or comparable enterprise platforms.</li></ul></div><div><ul><li>Experience with CI/CD, containers, APIs, infrastructure-as-code concepts, observability, and production incident management.</li></ul></div><div><p><b>
Success Profile</b></p></div><div><p>
A successful candidate will be a hands-on engineering lead who can take a generated or approved architecture, convert it into deployable assets, keep predictive AI models running reliably, and help the team move into applied AI delivery. The candidate should be comfortable doing implementation work across pricing and underwriting under senior supervision, while also raising the capability of junior engineers through practical technical guidance.</p><p><i>
This role will have a Hybrid work schedule, with the expectation of working in an office 3 days a week
</i></p><p><i>Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.</i></p></div><p><b>
Compensation</b></p><p>
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford&rsquo;s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:</p>
$117,200 - $175,800<p>
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age</p></div></div></div><p></p>

Senior AI Machine Learning Engineer

J2B GLOBAL LLC

<div><div><div><div><h3 class="jobSectionHeader"><b>Principal ML Engineer</b></h3>
</div><div>C2CContract
</div></div><div>Chicago, IL
</div><div>Visa: US CitizenH1BTNGreen CardGC-EADH4-EADEAD
</div><div>Role: Principal ML Engineer Location: Dallas, TX - 5 days onsite from day 1 Secondary locations: Chicago, IL and New York City, NY Job Description: Responsibilities: Contribute to Mail Intelligence Mission: Support the development of AI/ML capabilities that enhance user personalization and insights within Mail and the broader client's ecosystem. Innovate and Personalize: Assist in building scalable AI/ML solutions that identify user interests and habits, contributing to personalized user experiences. Technical Leadership: Guide and mentor a team of passionate engineers, fostering a culture of innovation and excellence. Your leadership will ensure the delivery of high-quality, user-centric solutions. Collaborative Development: Work with cross-functional teams to integrate new AI/ML features and improve existing platforms, ensuring smooth user interactions. Data-Driven Insights: Apply machine learning techniques and big data processing to derive insights from mail data, enhancing content and user knowledge. Tool and Workflow Development: Develop AI/ML tools and workflows to manage and utilize large datasets, supporting AI-based infrastructure and analytics. A/B Testing and Analysis: Run regular A/B tests, gather data, and draw conclusions on the impact of your models. Commitment to Excellence: Maintain high engineering standards, focusing on code quality and architectural skills, while delivering optimal user experiences. Feedback and Recovery: Implement feedback loops and recovery paths to handle AI failures gracefully, ensuring user satisfaction. Balance Tradeoffs: Manage cost, quality, and speed tradeoffs in AI/ML solutions to optimize performance. A lot about YOU Educational Background: You have a strong foundation in computer science, data science, or a related field, with a focus on machine learning and AI technologies. Technical Skills: Proficient in programming languages such as Python or Java and machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Skilled with AI tools such as Cursor, Copilot, and Claude. AI Skills: Advanced AI skills, including experience with AI development tools and frameworks. Problem-Solving Ability: You possess strong analytical skills and a knack for solving complex problems using data-driven approaches. Collaboration: You are a team player who can work effectively with cross-functional teams, including tech leads and architects, to deliver high-quality solutions. Passion for Innovation: You are enthusiastic about leveraging AI/ML to drive innovation and enhance user experiences across Mail and the broader ecosystem. Attention to Detail: You maintain high standards for code quality and are committed to delivering robust, scalable solutions. Continuous Learning: You are eager to stay updated with the latest advancements in AI/ML and apply them to improve products and services. Qualifications Educational Requirement: Bachelor's degree in Computer Science, Data Science, or a related field; a Master's degree is a plus. Experience: 8+ years of experience in machine learning, data analysis, or a related field. Technical Proficiency: Expertise in Python, Java, or C++ and machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Skilled with AI tools such as Cursor, Copilot, and Claude. Data and Infrastructure: Proficient in big data technologies (Hadoop, Spark) and modern ML infrastructure (Airflow, MLFlow, feature stores, vector databases, CI/CD for ML). Generative AI and Optimization: Hands-on experience with LLMs, generative AI (prompt engineering, Agent frameworks, fine-tuning, RAG, LLMOps), and GPU optimizations. Observability and Feedback: Familiar with observability, telemetry, and user feedback loops for product improvement. Algorithm Knowledge: Solid understanding of machine learning algorithms, natural language processing, and data mining techniques. Problem-Solving Skills: Demonstrated ability to solve complex problems and implement efficient, scalable solutions. Collaboration Skills: Ability to work effectively in a team environment and collaborate with tech leads, architects, and cross-functional teams. Communication Skills: Strong verbal and written communication skills to articulate complex technical concepts to non-technical stakeholders. Continuous Improvement: Eagerness to learn and adapt to new technologies and methodologies in the AI/ML domain. Preferred Qualifications Mail Experience: Prior experience working with email systems or related technologies is a plus. Personal Attributes: Self-driven and detail-oriented, with a passion for tackling challenges. Strong teamwork spirit, excellent communication skills, and the ability to multitask and manage expectations effectively. Cloud Experience: Experience with public cloud platforms, especially Google Cloud Platform (GCP), is preferred.</div></div><p></p><div><p> </p><p>Refer</p></div></div>

Principal ML Engineer

Indeed

<p>Our Mission<br/></p><p>As the world&rsquo;s number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and creating the best experience for job seekers.<br/></p><p>(*Comscore, Total Visits, March 2026)<br/></p><p>Day to Day<br/></p><p>As a Machine Learning Engineer III, you will be a team lead. Your role centers on leveraging AI/ML to ensure a seamless experience for job seekers. You will own one of the team&rsquo;s major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.<br/></p><p>Responsibilities<br/></p><p>Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.<br/>Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams<br/>Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.<br/>Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.<br/>Mentor and grow other software engineers and Machine Learning Engineers across teams<br/>Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them<br/>Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).<br/></p><p>Skills/Competencies<br/></p><p>Requires a Bachelor&rsquo;s degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master&rsquo;s degree with a minimum of 6 years of experience; or a PhD with 3 years experience<br/>Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams<br/>Solid knowledge of data structures and algorithms<br/>Sense of ownership and accountability as a key contributor in the technical and product domains<br/>Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)<br/>Excellent written and verbal communication in English, effective with technical and business audiences<br/></p><p>Eligibility Requirements:<br/></p><p>Candidates must be in one of the following Job Profiles: 11264 - Data Scientist II, 11265 - Data Scientist III or 11257 - Machine Learning Engineer II<br/>Candidates must be part of Marketplace Monetization Intelligence organization<br/></p><p>Salary Range Transparency<br/></p><p>Tier 1 - United States of America 163,000 - 245,000 USD per year<br/>Tier 2 - United States of America 182,000 - 272,000 USD per year<br/>Tier 3 - United States of America 199,000 - 299,000 USD per year<br/>Tier 4 - United States of America N/A<br/>Tier 5 - United States of America 227,000 - 341,000 USD per year<br/></p><p>Salary Range Disclaimer<br/></p><p>The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job-related skills, experience, and expertise, as evaluated during the interview process. The range(s) listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region-specific benefits. Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. Candidates can view geographic pay tiers by location on our career site (https://www.indeed.com/careers/paytiers), and recruiters can confirm how location is considered for a specific role.<br/></p><p>Benefits - Health, Work/Life Harmony, &amp; Wellbeing<br/></p><p>We care about what you care about. We have a multitude of benefits to support Indeedians, as well as their pets, kids, and partners including medical, dental, vision, disability and life insurance. Indeedians are able to enroll in our company&rsquo;s 401k plan, as well as an equity-based incentive program. Indeedians will also receive open paid time off, 11 paid holidays a year and up to 26 weeks of paid parental leave. For more information, select your country and learn more about our employee benefits, program, &amp; perks at https://www.indeed.com/careers/benefits!<br/></p><p>Equal Opportunities and Accommodations Statement<br/></p><p>Indeed is deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized. We&rsquo;re proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neuro-diversity, disability, age, or veteran status, or any other non-merit based or legally protected grounds.<br/></p><p>Indeed provides reasonable accommodations to qualified individuals with disabilities in the employment application process. To request an accommodation, please visit https://www.indeed.com/careers/accommodations. If you are requesting accommodation for an interview, please reach out at least one week in advance of your interview.<br/></p><p>For more information about our commitment to equal opportunity/affirmative action, please visit our Careers page (https://www.indeed.com/careers).<br/></p><p>Inclusion &amp; Belonging<br/></p><p>Inclusion and belonging are fundamental to our hiring practices and company culture, forming an integral part of our vision for a better world of work. At Indeed, we&rsquo;re committed to the wellbeing of our employees and on a mission to make this the best place to work and thrive. We believe that fostering an inclusive environment where every employee feels respected and accepted benefits everyone, fueling innovation and creativity.<br/></p><p>We value diverse experiences, including those who have had prior contact with the criminal legal system. We are committed to providing individuals with criminal records, including formerly incarcerated individuals, a fair chance at employment.<br/></p><p>Those with military experience are encouraged to apply. Equivalent expertise demonstrated through a combination of work experience, training, military experience, or education is welcome.<br/></p><p>Indeed&rsquo;s Employee Recruiting Privacy Policy<br/></p><p>Like other employers Indeed uses our own technologies to help us find and attract top talent from around the world. In addition to our site&rsquo;s user and privacy policy found at https://www.indeed.com/legal, we also want to make you aware of our recruitment specific privacy policy found at https://www.indeed.com/legal/indeed-jobs.<br/></p><p>Agency Disclaimer<br/>Indeed does not pay placement fees for unsolicited resumes or referrals from non-candidates, including search firms, staffing agencies, professional recruiters, fee-based referral services, and recruiting agencies (each individually, an &quot;Agency&quot;), subject to local laws. An Agency seeking a placement fee must obtain advance written approval from Indeed's internal Talent Acquisition team and execute a fee agreement with Indeed for each job opening before making a referral or submitting a resume for that opening.<br/></p><p>AI Notice<br/></p><p>Indeed is committed to ensuring fairness and transparency throughout our hiring process. We use artificial intelligence (AI) tools to assist in the screening, assessment, and selection of applicants for this position by analyzing information provided in resumes and applications. Our use of AI does not replace human decision-making.<br/></p><p>Unless otherwise notified, Indeed does not use AI constituting an AEDT or an ADMT as those tools are defined in applicable laws.<br/></p><p>Reference ID: 47478<br/></p><p>The deadline to apply to this position is 7/30/2026. Job postings may be extended at the hiring team&rsquo;s discretion based on applicant volume.<br/></p><p>It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.<br/></p><p>Reference ID: 47478<br/></p>

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