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Machine Learning Engineer Biotech Jobs in Boston, MA

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research into production-ready software. You'll partner closely with our Data Scientists, taking new ...

Manulife

Machine Learning Engineer

Boston, MA · Hybrid

$162K/yr

Machine Learning Engineer Job Duties: * Develop, build and maintain scalable data pipelines supporting underwriting, analytics, and machine learning systems; * Develop and deploy backend services and ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

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. You ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

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. You ...

ICONSTAFF

Machine Learning Engineer

Cambridge, MA · On-site +1

Machine Learning Engineer - Computer Vision & Robotics Tycho.AI is redefining the future of autonomous intelligence. Spun out of MIT and backed by DoD contracts, we are building breakthrough AI and ...

Capital One

Lead Machine Learning Engineer (IC)

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) 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.

XPO

Machine Learning Engineer - Hybrid

Boston, MA

$100K - $120K/yr

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

XPO

Machine Learning Engineer - Hybrid

Boston, MA

$100K - $120K/yr

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

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.

C the Signs

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data ...

C the Signs

Senior Machine Learning Engineer

Boston, MA · Remote

$125K - $165K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data ...

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All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Boston, MA

Machine Learning Engineer Biotech information

See Boston, MA salary details

$34.2K

$139.9K

$210.2K

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

As of Aug 31, 2026, the average yearly pay for machine learning engineer biotech in Boston, MA is $139,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,300.00 and $168,400.00 per year, depending on experience, location, and employer.

What does a machine learning engineer do in biotech?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do machine learning engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

What are the key skills and qualifications needed to thrive as a machine learning engineer in biotech?

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

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

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

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

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

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

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

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

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

Machine Learning Engineer Biotech jobs near you
Infographic showing various Machine Learning Engineer Biotech job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $139,895 per year, or $67.3 per hour.

Machine Learning Engineer

Burlington, MA • Remote

MatrixSpace
Computer Networking • 11 - 50 employees
Learn more about MatrixSpaceexternal

Full-time

Re-posted 24 days ago

Job description

Help us bridge machine learning research and real-world deployment!

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.
We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research into production-ready software. You'll partner closely with our Data Scientists, taking new algorithms and implementing them in performant, maintainable, and scalable production systems. You'll also help build the ML infrastructure and tooling that accelerates future research, while ensuring our AI solutions are reliable enough for real-world deployment.

If you're technically curious, highly collaborative, and motivated by solving complex real-world problems, we'd love to talk.

What You'll Do

  • Partner with Data Scientists to transform research algorithms into robust, production-quality software.
  • Implement machine learning algorithms in high-performance C++ and Python with a focus on maintainability, scalability, and real-time performance.
  • Build and improve machine learning infrastructure, tooling, and training pipelines that enable faster experimentation and more efficient model development.
  • Design and implement AI agents, agentic workflows, and LLM-powered applications.
  • Deploy and maintain AI workloads across edge, near-edge, and cloud environments.
  • Collaborate across engineering and research teams to transition prototypes into production systems.

What We're Looking For

This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.'

This is NOT a fully remote position!

Required

  • BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.
  • Strong hands-on programming experience in C++ and Python.
  • 3-5 years of experience developing and deploying machine learning systems in production environments.
  • Experience building AI agents, LLM-based applications, or intelligent automation systems.
  • Strong problem-solving skills and ability to work across the full development lifecycle.
  • Excellent written and verbal communication and collaboration skills.

Someone Who Will Thrive in This Role

  • Enjoys solving difficult technical challenges that span algorithms, software, and deployment.
  • Enjoys bridging the gap between research and production, finding practical engineering solutions that make advanced ML usable in real-world products.
  • Takes ownership and drives projects from concept through production.
  • Continuously explores new AI, ML, and agentic technologies.
  • Works effectively across multidisciplinary teams.
  • Balances research innovation with practical product delivery.
  • Builds side projects, experiments with emerging AI tools, or enjoys hands-on technical exploration.

Bonus Points

  • Experience with radar, RF sensing, sensor fusion, computer vision, robotics, or autonomous systems.
  • Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.
  • Experience optimizing models for edge deployment usingTensorRT, ONNX,OpenVINO, TVM, or similar tools.
  • Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration.
  • Familiarity withMLOps, CI/CD, model monitoring, and large-scale production systems.

At MatrixSpace, Machine Learning Engineering is where advanced AI research becomes real-world capability. This is an engineering-heavy ML role focused on productionizing algorithms created by Data Scientists, with some ownership of the ML infrastructure that helps those Data Scientists move faster.