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Sr Machine Learning Engineer Jobs in Massachusetts

Sierra Ventures

Machine Learning Engineer

Somerville, MA · On-site

$170 - $200/hr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting‑edge machine ...

Capital One

Sr. Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Sr. 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.

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All JobsSr Machine Learning Engineer JobsSr Machine Learning Engineer Jobs in Massachusetts

Sr Machine Learning Engineer information

See Massachusetts salary details

$65K

$138.2K

$200.4K

How much do sr machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for sr machine learning engineer in Massachusetts is $138,216.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $156,700.00 per year, depending on experience, location, and employer.

What is a Sr Machine Learning Engineer?

Senior Machine Learning Engineers are experienced professionals who design, develop, and implement machine learning models and systems. They work on complex problems, lead technical projects, and often mentor junior engineers. Their responsibilities include data preprocessing, model selection, algorithm development, and optimizing solutions for scalability and performance. Senior ML Engineers also collaborate closely with data scientists, software engineers, and stakeholders to integrate machine learning into products and services.

What are the key skills and qualifications needed to thrive as a Sr Machine Learning Engineer?

To thrive as a Sr Machine Learning Engineer, you need advanced expertise in machine learning theory, programming (Python, R), data modeling, and a strong background in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP), and relevant certifications (like TensorFlow Developer) is highly beneficial. Strong problem-solving skills, effective communication, and the ability to lead and mentor teams set top candidates apart. These skills ensure the ability to design scalable ML solutions, collaborate effectively, and drive impactful business outcomes.

How does a Sr Machine Learning Engineer typically collaborate with data scientists and software engineers within a project team?

Sr Machine Learning Engineers frequently act as a bridge between data scientists, who focus on model development and experimentation, and software engineers, who handle system integration and production deployment. They translate prototype models into scalable, production-ready solutions, ensuring that models are optimized for real-world performance. Collaboration often involves reviewing code, aligning on data pipeline requirements, and participating in regular team meetings to address technical and business objectives. This cross-functional teamwork is essential for delivering reliable machine learning products.

What is the difference between Sr Machine Learning Engineer vs Data Scientist?

AspectSr Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, ML, or related fields; experience with ML frameworksBachelor's/Master's/PhD in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds models, interprets data insights for business
Industry UsageTech, finance, healthcare, e-commerceResearch, marketing, finance, tech

While both roles involve working with data and models, Sr Machine Learning Engineers focus on building and deploying scalable ML systems, whereas Data Scientists primarily analyze data and develop insights. The roles often overlap but differ in technical focus and responsibilities.

What are popular job titles related to Sr Machine Learning Engineer jobs in Massachusetts?

For Sr Machine Learning Engineer jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Sr Machine Learning Engineer jobs in Massachusetts look for?

The top searched job categories for Sr Machine Learning Engineer jobs in Massachusetts are:

Sr Machine Learning Engineer jobs near you
Infographic showing various Sr Machine Learning Engineer job openings in Massachusetts as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $138,216 per year, or $66.5 per hour.

Senior Machine Learning Engineer (Health)

Mass Digital Health

Boston, MA • On-site

$120 - $160/hr

Other

Posted 17 days ago

Key responsibilities

  • Create, improve, and maintain production services that provide analysis for health features.

  • Collaborate with Data Engineers to improve ML data pipelines, tooling, and validation systems.

  • Work alongside data scientists to translate research prototypes into production ML systems optimized for scale, latency, and cost efficiency.

Job description

WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance and healthspan. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives.

Health team is responsible for developing novel algorithms and features that expand our health capabilities. Our work spans several key areas, including women’s health, medical device–grade metrics, wellness monitoring, longevity research, and emerging health insights. We combine continuous physiological data with clinical research and expert knowledge to generate features that are both scientifically grounded and deeply impactful for members.

Senior Machine Learning Engineer on our Health team, you will design, build, and productionize ML systems that deliver meaningful, personalized health metrics to millions of members. You will work at the intersection of data science, backend engineering, and cloud infrastructure—deploying robust, scalable, and reliable ML solutions built on physiological and behavioral data streams. This role emphasizes strong coding skills, system design, and the ability to deliver production-ready ML services.

RESPONSIBILITIES:
  • Create, improve, and maintain production services that provide analysis for health features in collaboration with Data Scientists and MLOps Engineers.
  • Collaborate with Data Engineers to improve ML data pipelines, tooling, and validation systems that support robust model performance.
  • Work alongside data scientists to translate research prototypes into production ML systems optimized for scale, latency, and cost efficiency.
  • Collaborate with researchers and product teams to align model development with health insights and member impact.
  • Participate in on-call rotations for data science services, ensuring uptime and performance in production environments.
QUALIFICATIONS:
  • Bachelor’s Degree in Computer Science, Data Science, Applied Mathematics, or a related field. Master’s preferred.
  • 5+ years of professional experience as a Machine Learning Engineer or Software Engineer with focus on ML systems.
  • Proven expertise working with time series data (wearable, physiological, or high-frequency sensor data strongly preferred).
  • Experience designing and deploying ML inference systems at scale: both real-time streaming and large-scale batch pipelines.
  • Strong coding skills in Python (scientific stack) and SQL, with a track record of writing clean, production-quality code.
  • Strong communication skills to collaborate across engineering, research, and product teams.
  • Proven experience deploying and maintaining ML systems on cloud platforms (AWS or GCP)
  • Working familiarity with MLOps best practices: model versioning, CI/CD for ML, observability, and monitoring for inference systems.
  • Ability to reason about and design for performance trade-offs (latency vs. throughput vs. cost) when building ML inference systems.
  • Strong understanding of backend service development (APIs and service reliability) as it applies to serving ML models at scale.

This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.

WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. 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.

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