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Remote Machine Learning Biology Jobs in California

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

DocuSign

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 ... Employee divides their time between in-office and remote work. Access to an office location is ...

Autodesk

Senior Machine Learning Engineer

San Francisco, CA · On-site +1

$123K - $169K/yr

This role is currently open to remote work. Candidates must be located near one of our hub ... Design and implement machine learning capabilities that improve Autodesk's customer-facing ...

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Remote Machine Learning Biology information

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Biology professional, and why are they important?

To thrive as a Remote Machine Learning Biology professional, you need a strong foundation in computational biology, machine learning algorithms, programming (such as Python or R), and a relevant degree in bioinformatics, computer science, or biology. Familiarity with bioinformatics tools, data analysis platforms, cloud computing resources, and frameworks like TensorFlow or PyTorch is typically required. Excellent problem-solving, collaboration, and communication skills are essential for effectively interpreting results and working with interdisciplinary teams in a remote environment. These skills and qualities are crucial for advancing biological research through data-driven insights and ensuring effective teamwork and project delivery in a virtual setting.

What is the difference between Remote Machine Learning Biology vs Remote Bioinformatics Specialist?

AspectRemote Machine Learning BiologyRemote Bioinformatics Specialist
Required CredentialsMaster's or PhD in Biology, Data Science, or related fields; experience in machine learningBachelor's or Master's in Bioinformatics, Biology, or Computer Science; programming skills
Work EnvironmentResearch labs, biotech companies, or academic institutions with remote optionsResearch institutions, healthcare, or biotech firms with remote roles
Industry UsageUsed in biotech, pharmaceuticals, and research to analyze biological data with MLApplied in genomics, proteomics, and clinical data analysis

Remote Machine Learning Biology focuses on applying machine learning techniques to biological data, often requiring advanced degrees and programming skills. Remote Bioinformatics Specialists analyze biological datasets using bioinformatics tools. Both roles are vital in biotech and research industries, but they differ in technical focus and required expertise.

How do remote machine learning biology professionals typically collaborate with experimental biologists and other team members?

Remote machine learning biology professionals often work closely with experimental biologists, bioinformaticians, and data engineers through virtual meetings, shared project management tools, and collaborative coding platforms. Regular communication is vital to ensure alignment on research objectives, data requirements, and interpretation of results. Team members typically share data, code, and experimental findings using cloud-based repositories, while frequent check-ins help address challenges and maintain project momentum. This collaborative approach allows remote professionals to contribute effectively to interdisciplinary research, despite physical distance.

What is a Remote Machine Learning Biologist?

A Remote Machine Learning Biologist is a professional who applies machine learning techniques to biological data and problems while working remotely, often from home or a location outside a traditional laboratory or office. They use computational tools and algorithms to analyze complex biological datasets, such as genomics, proteomics, or drug discovery data, to derive insights or make predictions. Their work may involve developing predictive models, automating data analysis, and collaborating with life scientists and engineers. Remote roles in this field require strong skills in both biology and computer science, as well as the ability to work independently and communicate effectively with remote teams.
What are the most commonly searched types of Machine Learning Biology jobs in California? The most popular types of Machine Learning Biology jobs in California are:
What are popular job titles related to Remote Machine Learning Biology jobs in California? For Remote Machine Learning Biology jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Biology jobs in California look for? The top searched job categories for Remote Machine Learning Biology jobs in California are:
What cities in California are hiring for Remote Machine Learning Biology jobs? Cities in California with the most Remote Machine Learning Biology job openings:
Remote Machine Learning Biology jobs near you
Infographic showing various Remote Machine Learning Biology job openings in California as of June 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution.

Machine Learning Engineer

PhysicsX

San Francisco, CA • On-site, Remote

Other

Medical, Retirement, PTO

Posted 11 days ago

Job description

Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.

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 industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
You've shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area.

This Role 

As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.

What you will do
  • Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
  • Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
  • Explore and manipulate 3D point cloud & mesh data
  • Own the delivery of technical workstreams
  • Create analytics environments and resources in the cloud or on premise, spanning data engineering and science
  • Identify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for success
  • Work at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and products
  • Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption
You'll also have the opportunity to travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
 
What you bring to the table
  • Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods) to real-world engineering applications, with a focus on driving measurable impact in industry settings.
  • Experience in ML/Computational statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes) is encouraged.
  • A track record of scoping and delivering projects in a customer facing role
  • 2+ years' experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
  • Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)
  • Distributed computing frameworks (e.g., Spark, Dask)
  • Cloud platforms (e.g., AWS, Azure, GCP) and HP computing
  • Containerization and orchestration (Docker, Kubernetes)   
  • Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
  • Excellent collaboration and communication skills - with teams and customers alike
  • A background in Physics, Engineering, or equivalent
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you'll contribute to this exciting journey! What we offerBuild what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you're ambitious, thoughtful, and driven by impact, you'll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn't just welcomed, it's expected.

And it doesn't stop there ...

 Equity options - share meaningfully in the company you're helping to build.

 5% contribution to 401(k) - build long-term security with a strong retirement plan.

 Private health insurance - comprehensive cover for you, offering total peace of mind.

 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

 Personal development - dedicated support for learning, development, and leveling up over time.

 Gympass / Wellhub (subsidized) - for you and up to 3 family members, supporting both physical and mental wellbeing.

 Flexible Spending Account (FSA) - set aside pre-tax dollars for eligible healthcare expenses.

Watch this space, we're continuing to build this as we grow...

Salary range:

$150,000 - $190,000 depending on experience 
Seniority will be assessed throughout our interview process 

Apply