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Machine Learning Engineer Opt Jobs in Stoneham, MA

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 ...

Senior Machine Learning Engineer

Boston, MA

$133K - $175K/yr

The Crown Is Yours As a Senior Machine Learning Engineer, you'll design, implement, and scale production-grade data and machine learning pipelines that drive measurable business outcomes. You'll ...

Senior Machine Learning Engineer

Boston, MA · On-site

$133K - $175K/yr

The Crown Is Yours As a Senior Machine Learning Engineer, you'll design, implement, and scale production-grade data and machine learning pipelines that drive measurable business outcomes. You'll ...

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

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 ...

Machine Learning Engineer - Cloud

Lowell, MA · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Cloud *Please consider before applying: This is a hybrid role, and candidates must reside within a commutable distance of one of our offices in either Dover, NH, or Lowell ...

Senior Machine Learning Engineer The Opportunity Join John Hancock's AI team and help transform the insurance experience through advanced analytics and intelligent automation. You'll work at the ...

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 ...

As a ML engineer with the Alexa AI team, you will be responsible for machine learning platform focus on LLM training, production deployment, and optimizations to advance the state of LLMs. You will ...

Senior Machine Learning Engineer

Andover, MA · On-site

$105K - $145K/yr

They are seeking a Senior Machine Learning Engineer to join their Analytics team, focusing on building data science products that enhance game design and player engagement. Responsibilities : • ...

Machine Learning Engineer

Boston, MA · On-site +1

$136K - $225K/yr

Apply standard software engineering practices, including version control, code reviews, and collaborative development workflows. * Implement basic testing and validation to ensure correctness and ...

Showing results 41-60

Machine Learning Engineer Opt information

See Stoneham, MA salary details

$34.5K

$140.9K

$211.8K

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

As of Jul 24, 2026, the average yearly pay for machine learning engineer opt in Stoneham, MA is $140,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,100.00 and $169,600.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What cities near Stoneham, MA are hiring for Machine Learning Engineer Opt jobs? Cities near Stoneham, MA with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer II / Senior Machine Learning Engineer I, Physical Sciences

Lila Sciences

Cambridge, MA

$114K - $156K/yr

Other

Posted 20 days ago


Job description

Your Impact at LILA

This Machine Learning Engineer for the Physical Sciences team focuses on building and operating end-to-end, scalable machine learning workflows that solve a diversity scientific use cases in materials, chemistry and physical sciences. Your work will advance research efforts on state-of-the-art algorithms to build towards scientific superintelligence across today's greatest challenges in physical sciences.

What You'll Be Building

  • Design, implement, and maintain endtoend ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring).
  • Productionize models and services with robust testing, observability, and documentation in collaboration with cross-functional software teams and build CI/CD workflows and automated evaluations to ensure safe, frequent releases.
  • Collaborate with domain scientists and platform engineers to translate research insights into performant, scalable systems.
  • Contribute to technical design reviews, coding standards, and mentoring of best practices.

What You'll Need to Succeed

  • BS/MS/PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
  • Strong Python software engineering fundamentals (testing, packaging, typing); experience with machine learning frameworks (e.g., PyTorch, Huggingface, etc.).
  • Experience deploying ML services to production in cloud-based infrastructure (FastAPI/GRPC, containers, orchestration, cloud infra).
  • Handson experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
  • Clear communication and collaboration in crossfunctional settings.

Bonus Points For

  • Exposure to scientific or engineering domains (materials, chemistry, physics) and related data formats/benchmarks.
  • GPU optimization experience (CUDA, Triton, compilation, distributed training).
  • Prior contributions to opensource ML or scientific software.
  • Experience with workflow orchestration, data provenance, or largescale compute environments.