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Machine Learning Engineer Biotech Jobs in Berkeley, CA

Blank Bio

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will be responsible for scaling models, building training infrastructure, and ensuring reproducibility across large-scale biological datasets while collaborating with ...

Jobzhr

Machine Learning Engineer

Pleasanton, CA · On-site

$110 - $150/hr

... with machine learning frameworks such as TensorFlow, Keras, and PyTorch. Knowledge of cloud platforms and technologies, specifically Microsoft Azure, is crucial. Experience in DevOps and MLOps ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

OpenReq

Machine Learning Engineer

San Francisco, CA · On-site

As a Machine Learning Engineer, you will shape the technical direction of the company by automating the ML life-cycle and engaging directly with customers while contributing to the architectural ...

Reducto

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to train and deploy critical models for their core product, focusing on interpreting unstructured data and improving model performance. Responsibilities ...

Menlo Ventures

Machine Learning Engineer

San Mateo, CA · On-site

$195 - $350/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

We're hiring a Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high‑stakes legal work -- from intake ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

$180 - $260/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Opportunity We are building a platform for AI Agents to come together and solve arbitrarily complex tasks, leveraging Superhuman ubiquitous UI. As a Machine Learning Engineer on this team, you ...

Jobzhr

Machine Learning Engineer, Drive

San Francisco, CA · On-site

$204 - $299/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

About The Role As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end--from feature engineering and model development to experimentation, deployment ...

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Showing results 41-60

All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Berkeley, CA

Machine Learning Engineer Biotech information

See Berkeley, CA salary details

$38.6K

$157.7K

$236.9K

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

As of Aug 16, 2026, the average yearly pay for machine learning engineer biotech in Berkeley, CA is $157,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,300.00 and $189,800.00 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 Berkeley, CA?

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

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

The top searched job categories for Machine Learning Engineer Biotech jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Machine Learning Engineer Biotech jobs?

Cities near Berkeley, CA 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 Berkeley, CA as of August 2026, with employment types broken down into 8% Internship, and 92% Full Time. Highlights an 68% In-person, 21% Hybrid, and 11% Remote job distribution, with an average salary of $157,670 per year, or $75.8 per hour.

Machine Learning Engineer

Blank Bio

San Francisco, CA • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Blank Bio is an applied AI research lab focused on increasing the success rates of clinical trials by training RNA foundation models. The Machine Learning Engineer will be responsible for scaling models, building training infrastructure, and ensuring reproducibility across large-scale biological datasets while collaborating with research scientists and biologists.
Responsibilities:
• Develop and optimize large-scale ML training pipelines for RNA foundation models.
• Implement distributed training systems (multi-GPU/TPU) and optimize performance at scale.
• Build infrastructure for dataset management, preprocessing, and benchmarking.
• Collaborate with scientists to translate biological questions into ML tasks.
• Contribute to the design and evaluation of new architectures, embeddings, and fine-tuning strategies.
• Maintain high-quality engineering standards, including reproducibility, testing, and deployment readiness.
Qualifications:
Required:
• 3+ years of work experience
• Proficiency in Python and modern deep learning frameworks (PyTorch, JAX, or TensorFlow).
• Hands-on experience training large-scale models (transformers, diffusion, or sequence models).
• Strong background in distributed training, optimization, and performance profiling.
• Track record of building ML systems that scale and ship.
Preferred:
• Experience with biological or messy, real-world scientific data.
• Background in computational biology, bioinformatics, or adjacent fields.
• Experience in early-stage startups or interdisciplinary ML-for-science projects.
Company:
Blank Bio is an applied AI research company developing RNA foundation models that analyze biological sequence data for therapeutic research. Founded in 2025, the company is headquartered in San Francisco, USA, with a team of 2-10 employees. The company is currently Early Stage.

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