ZipRecruiter

Log In

1

Machine Learning Engineer Biotech Jobs in Annapolis, MD

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

About the Role We are seeking a Machine Learning Engineer to design, build, and evaluate advanced machine learning systems across AI safety and model evaluation applications. This role combines ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the next-generation data management and artificial intelligence platform for maritime domain awareness.

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$180 - $240/hr

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM Ops, and SecDevOps practices, resulting in an exciting, fast-paced engineering role. This role ...

previous pagenext page

Showing results 21-40

All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Annapolis, MD

Machine Learning Engineer Biotech information

See Annapolis, MD salary details

$31.2K

$127.5K

$191.6K

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

As of Sep 5, 2026, the average yearly pay for machine learning engineer biotech in Annapolis, MD is $127,472.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $153,400.00 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 popular job titles related to Machine Learning Engineer Biotech jobs in Annapolis, MD?

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

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

The top searched job categories for Machine Learning Engineer Biotech jobs in Annapolis, MD are:

What cities near Annapolis, MD are hiring for Machine Learning Engineer Biotech jobs?

Cities near Annapolis, MD with the most Machine Learning Engineer Biotech job openings:

Machine Learning Engineer Biotech jobs near you
Infographic showing various Machine Learning Engineer Biotech job openings in Annapolis, MD as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 78% Physical, 2% Hybrid, and 20% Remote job distribution, with an average salary of $127,472 per year, or $61.3 per hour.

Machine Learning Engineer

10a Labs

Washington, DC • On-site, Remote

$130K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

This job post has expired today. Applications are no longer accepted.

Job description

About the Role

We are seeking a Machine Learning Engineer to design, build, and evaluate advanced machine learning systems across AI safety and model evaluation applications.

This role combines strong ML engineering with an experimental mindset. You will work on problems involving reinforcement learning, model evaluations, language models, multimodal systems, and classifiers, taking ambiguous technical questions and turning them into rigorous experiments and scalable systems.

You will collaborate closely with engineers, analysts, red teamers, and subject-matter experts supporting leading AI organizations.

What You'll Do
  • Design and run ML experiments to evaluate the capabilities, behavior, robustness, and limitations of advanced AI systems.
  • Develop and evaluate models across reinforcement learning, NLP/LLMs, computer vision, and multimodal ML.
  • Build evaluation pipelines, benchmarks, datasets, and metrics for frontier AI systems.
  • Train, fine-tune, and evaluate models for safety, security, and other high-impact applications.
  • Develop reliable tooling and infrastructure to run ML experiments and evaluations at scale.
  • Analyze results, identify model failure modes, and translate findings into new experiments and technical approaches.
What We're Looking For
  • 3-5+ years of experience in machine learning, research engineering, or a related technical field.
  • Strong Python skills and experience with ML frameworks such as PyTorch or JAX.
  • Hands-on experience training, fine-tuning, or evaluating modern ML models.
  • Strong understanding of experimental design, model evaluation, and quantitative analysis.
  • Familiarity with agentic AI fundamentals, including common harnesses, Model Context Protocol, agent benchmarks, and security risks to AI agents.
  • Experience in one or more of the following: reinforcement learning, NLP/LLMs, computer vision, or multimodal ML.
  • Strong software engineering fundamentals and the ability to work independently on ambiguous technical problems.
Nice to Have
  • Experience with RLHF/RLAIF, reward modeling, policy optimization, or other model post-training techniques.
  • Experience evaluating frontier language or multimodal models.
  • Experience with adversarial evaluations, robustness testing, or AI safety.
  • Experience with distributed training, cloud ML infrastructure, or large-scale ML systems.

We don't expect candidates to have experience across every area above. We value deep ML expertise, strong experimental instincts, and the ability to quickly learn new techniques.

Compensation & Benefits
  • Salary Range: $130K-$200K, depending on experience and location
  • Bonus: Performance-based annual bonus
  • Professional Development: Support for conferences, continuing education, or leadership training
  • Work Environment: Fully remote, U.S.-based
  • Health Benefits: Comprehensive health, dental, and vision coverage
  • Time Off: Generous PTO and paid holiday schedule

Apply