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Machine Learning Engineer Jobs in Lowell, MA (NOW HIRING)

VideaHealth

Senior Machine Learning Engineer

Boston, MA · On-site

$170K - $205K/yr

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

Overview: The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global research and development team. This role centers on leading the design and delivery of ...

OneStudyTeam

Senior Machine Learning Engineer

Boston, MA · Remote

$140K - $190K/yr

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in building cutting-edge AI products that directly impact how new therapies reach patients. We're looking for ...

CVS Health

Senior Machine Learning Engineer

Wellesley, MA · On-site

$111K - $222K/yr

We're looking for a Senior Machine Learning Engineer to help build and scale the next generation of data science and AI products in the journey. In this role, you'll leverage your engineering ...

Crowe-Global

Machine Learning Engineer

Boston, MA · On-site

$62 - $100/hr

About the RoleAs an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves ...

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OneScreen

Founding Machine Learning Engineer

Boston, MA · On-site

About the role You'll be the founding ML engineer who owns our matching algorithms from exploration ... Real ranking and matching modeling fluency - learning-to-rank, retrieval and re-rank patterns, not ...

Cognex

Senior Machine Learning Engineer

Natick, MA · On-site

$115K - $225K/yr

Cognex is a global leader in the exciting and growing field of machine vision. Our employees ... Job Summary We are seeking an experienced AI/ML engineer with strong research and developmentskills ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Lowell, MA

Machine Learning Engineer information

See Lowell, MA salary details

$31.2K

$127.7K

$191.9K

How much do machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning engineer in Lowell, MA is $127,709.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,700.00 and $153,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What are the most commonly searched types of Machine Learning Engineer jobs in Lowell, MA?

The most popular types of Machine Learning Engineer jobs in Lowell, MA are:

What are popular job titles related to Machine Learning Engineer jobs in Lowell, MA?

For Machine Learning Engineer jobs in Lowell, MA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Lowell, MA look for?

The top searched job categories for Machine Learning Engineer jobs in Lowell, MA are:

What cities near Lowell, MA are hiring for Machine Learning Engineer jobs?

Cities near Lowell, MA with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Lowell, MA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,709 per year, or $61.4 per hour.

Senior Machine Learning Engineer

VideaHealth

Boston, MA • On-site

$170K - $205K/yr

Full-time

PTO

Re-posted 5 days ago

Job description

About us:
Videa is a cutting-edge AI-powered solution for dentistry, developed by a team of seasoned leaders, engineers, AI scientists, and clinicians spun out of MIT. Our vision is to be the first company to diagnose a billion people globally. Our product is already used by thousands of dental clinicians to enhance the quality of care through faster diagnoses, to increase operating efficiencies, and to improve patient understanding.
About the position:
We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer vision teams. This is an opportunity to design, build, and scale machine learning systems that combine structured clinical data with outputs from our core computer vision models to improve patient care and operational performance.
You'll own end-to-end development of production ML systems, integrate them safely into healthcare workflows, and deploy reliable, interpretable, and monitored models that meet medical-grade standards. Depending on your background, that might mean predictive and tabular modeling, multimodal systems, large-scale training and inference infrastructure, model evaluation and reliability, or another specialty where you bring real depth. You'll work alongside ML scientists, clinical experts, and product engineers to translate real clinical questions into systems that ship and hold up over time.
We're looking for a hands-on builder who's excited to work with real-world clinical data, get models into production, and own them across their full lifecycle. If you care about impact and want to help define the future of applied AI in healthcare, we'd love to meet you.
Key Responsibilities:
  • Design, build, and deploy production ML systems for clinical decision support and operational insight, applying deep expertise from your area of specialty.
  • Develop ML pipelines that integrate structured clinical or EHR data with outputs from computer vision models to power downstream applications.
  • Ensure the calibration, robustness, and interpretability of deployed models, including clear clinician-facing explanations where relevant.
  • Implement monitoring, drift detection, evaluation protocols, and retraining or update workflows for production systems.
  • Partner cross-functionally with product, engineering, clinical, and compliance teams to define requirements and integrate models into live workflows.
  • Contribute to regulatory documentation for ML systems (data descriptions, validation reports, model versioning).
  • Mentor engineers and help establish best practices for applied ML and experimentation.
Requirements
  • 4+ years building and deploying machine learning systems in production, ideally with real-world or clinical data.
  • Deep, demonstrable expertise in at least one area of ML engineering, such as predictive and tabular modeling, multimodal systems, training and inference infrastructure, or model evaluation and reliability, along with the breadth to contribute across the stack.
  • Strong development skills in Python with testing, CI/CD, and collaborative coding practices.
  • Exceptional critical thinking and problem decomposition. Able to turn ambiguous clinical or business questions into measurable hypotheses, design sound experiments, and reason clearly about trade-offs between accuracy, reliability, interpretability, and operational impact.
  • Familiarity with production ML practices, including monitoring data drift, performance over time, and model health.
  • Excellent communication skills and a collaborative, product-oriented mindset.
Preferred
  • M.S. or Ph.D. in a relevant technical field.
  • Experience with healthcare data or regulated ML systems.
  • Background in multimodal or stacked models, especially combining CV outputs with tabular data.
  • Familiarity with survival analysis, time-series, or longitudinal modeling.
  • Open-source contributions or published work in applied ML.
  • Prior leadership or mentorship experience

What We Offer
  • Fast paced and collaborative work culture in which you can gain experience, grow your technical skills and work on a wide variety of challenges over your time with us
  • Competitive pay, equity and benefits (flexible PTO)
  • Agile organization where being senior translates to being a mentor and role model for others. We lead by example.
  • Technical challenges on the leading edge of innovation where software and machine learning intersect.

Videa is supported by some of the best investors in the world, having raised over $67M in Venture Capital from Tier 1 investors such as Spark Capital (Twitter, SnapChat, SmileDirectClub), Zetta Venture (Kaggle), and Pillar VC (PillPack), as well as angel investors such as Frederic Kerrest (Co-founder of Okta). Our work has been featured in TechCrunch, Wall Street Journal, and many other outlets.
If you want to join a breakthrough healthtech company and help accelerate its impact and growth, we encourage you to apply for this exciting opportunity!

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