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Senior Machine Learning Engineer Jobs in Massachusetts

Sierra Ventures

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

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 ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

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 JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Massachusetts

Senior Machine Learning Engineer information

See Massachusetts salary details

$65K

$138.2K

$200.4K

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

As of Sep 15, 2026, the average yearly pay for senior 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 does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Massachusetts?

The most popular types of Machine Learning Engineer jobs in Massachusetts are:

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

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

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

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

What cities in Massachusetts are hiring for Senior Machine Learning Engineer jobs?

Cities in Massachusetts with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $138,216 per year, or $66.5 per hour.

Senior Machine Learning Engineer (Health)

Boston, MA • On-site

Mass Digital Health
See more jobs at Mass Digital Healthexternal

$113K - $155K/yr

Other

Posted 27 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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