1

Machine Learning Engineer Biotech Jobs in Berkeley, CA

Machine Learning Engineer At Krea, we are building next-generation AI creative tools. We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that ...

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

Machine Learning Engineer We are looking for a Machine Learning Engineer to join the growing AI and Machine Learning team at Strava. This team is responsible for sophisticated machine learning models ...

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of key technologies and ...

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Machine Learning Engineer Fremont, California Gotion Inc. is based in Silicon Valley, CA, currently building a Manufacturing facility in Manteno, IL and has R&D centers in Ohio, China, Japan and ...

Machine Learning Engineer

San Francisco, CA · On-site

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

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 ...

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

next page

Showing results 1-20

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 Jun 14, 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 the biotech industry?

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, and why are they important?

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 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:
Infographic showing various Machine Learning Engineer Biotech job openings in Berkeley, CA as of June 2026, with employment types broken down into 18% Internship, and 82% Full Time. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $157,670 per year, or $75.8 per hour.

Machine Learning Engineer

Krea

San Francisco, CA

Other

Posted 5 days ago


Job description

Machine Learning Engineer

At Krea, we are building next-generation AI creative tools.

We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.

We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium.

We're looking for a machine learning engineer who can work on large-scale image and video models training experiments.

Some stuff you can do:

  • Train foundation diffusion models for image and video generation.
  • Train controllability modules such as IPAdapters or ControlNets.
  • Develop novel research techniques and put them into production.
  • Conducting large-scale experiments on high-performance computing clusters, optimizing data pipelines for massive image datasets

Example experience and skills we're looking for:

  • Proven track record in working with image or video models at scale (publications or open-source contributions a plus)
  • Strong background in deep learning frameworks and distributed training paradigms.
  • Ability to iterate rapidly, and propose creative research directions

A bit more about us:

We've raised over $83M and are backed by world-class Silicon Valley investors such as Andreessen Horiwitz, and the cofounder of the Meta AI Research laboratory (FMK as Facebook AI Research) or founding members of OpenAI.