ZipRecruiter

Log In

1

Machine Learning Engineer Python Jobs in Beverly, MA

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 ... Strong development skills in Python with testing, CI/CD, and collaborative coding practices.

Draper

Senior Machine Learning Engineer

Cambridge, MA · On-site +1

$82K - $220K/yr

Summary: The Machine Learning Engineer (SMTS) designs and implements machine learning (ML ... Strong ML/AI software development skills (Python, MATLAB, R, C++, JAVA) including software best ...

Manulife

Senior Machine Learning Engineer

Boston, MA · On-site

$107K - $199K/yr

Senior Machine Learning Engineer The Opportunity Join John Hancock's AI team and help transform the ... Strong programming skills in Python (Java/SQL a plus) * Hands-on experience with NLP and document ...

GN Group

Machine Learning Engineer - Cloud

Lowell, MA · On-site +1

$86K - $135K/yr

Proficiency in programming languages such as Python, R, Java, or C++ for developing and optimizing machine learning algorithms. * Familiarity with big data technologies and distributed computing ...

next page

Showing results 1-20

All JobsMachine Learning Engineer Python JobsMachine Learning Engineer Python Jobs in Beverly, MA

Machine Learning Engineer Python information

See Beverly, MA salary details

$25.4K

$154.5K

$223.5K

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

As of Jul 16, 2026, the average yearly pay for machine learning engineer python in Beverly, MA is $154,491.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,000.00 and $181,600.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is the salary of machine learning engineer in Python?

The average salary for a machine learning engineer proficient in Python typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those requiring specialized skills in deep learning or data engineering may offer higher compensation.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Python, and why are they important?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What engineer makes $500,000 a year?

A senior or lead machine learning engineer with extensive experience, advanced skills in Python, deep learning, and data modeling can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Such roles often require advanced degrees, certifications, and a strong track record of successful projects.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI director, often involving advanced skills in Python, deep learning, and data science. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in competitive industries like tech or finance.

Is Python enough for ML engineers?

Python is a fundamental programming language for machine learning engineers due to its extensive libraries like TensorFlow, PyTorch, and scikit-learn. However, proficiency in data manipulation, algorithms, and understanding of machine learning concepts, along with knowledge of tools like SQL and cloud platforms, are also important for success in the role.
What cities near Beverly, MA are hiring for Machine Learning Engineer Python jobs? Cities near Beverly, MA with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

VideaHealth

Boston, MA • On-site

$170K - $205K/yr

Full-time

PTO

Posted 28 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!

Apply