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Remote Machine Learning Biology Jobs in California

Profluent

Machine Learning Scientist, BioML

Emeryville, CA · On-site +1

$200K - $330K/yr

Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all ... We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into ...

Unitytech

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

AbbVie

Machine Learning Engineer

San Diego, CA · On-site +1

$109K/yr

Own small to medium components of machine learning systems from technical designthrough ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

AbbVie

Machine Learning Engineer

San Diego, CA · On-site +1

Own small to medium components of machine learning systems from technical designthrough ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

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All JobsMachine Learning Biology JobsRemote Machine Learning Biology JobsRemote Machine Learning Biology Jobs in California

Remote Machine Learning Biology information

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 key skills and qualifications needed to thrive as a remote machine learning biology professional?

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.

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 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.

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 August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 23 days ago

Job description

Our client is a leader in healthcare innovation, seamlessly integrating pharmaceutical development, diagnostic solutions, and advanced technology and data capabilities.
Title: Machine Learning Engineer (Contract)
Pay rate: $55-73/hr+ (Depends on experience)
Location: Remote in the US or Canada, or onsite in SSF. Must be available during PST hours.
Duration: Through Dec. 2026 (Likely to get extended)
Overview:
Seeking a Machine Learning Bioinformatics Engineer to develop and deploy advanced ML solutions supporting pharmaceutical R&D. This role focuses on analyzing large-scale, multimodal clinicogenomic datasets (genomic, transcriptomic, clinical, and real-world data) to drive insights into disease biology, patient stratification, and treatment response. Ideal candidates are strong in both machine learning and bioinformatics, with a passion for translating complex data into impactful discoveries.
Key Responsibilities:
  • Build and deploy scalable, production-ready machine learning models
  • Process and analyze genomic and transcriptomic data using bioinformatics pipelines
  • Prepare high-quality, normalized biological datasets for downstream analysis
  • Train large-scale models using frameworks like PyTorch Lightning and Hugging Face
  • Develop cloud-based ML solutions (AWS/GCP) with a focus on scalability and reproducibility
  • Collaborate with cross-functional teams to uncover biomarkers and therapeutic targets
  • Provide technical input and guidance on ML system design and implementation

Qualifications:
  • PhD with 0-2 years of relevant work experience, or MS with 3-5 years of relevant work experience, or BS with 4-7 years of relevant work experience.
  • Proficient programming skills: Strong Python programming skills with extensive experience in ML and data libraries (e.g., NumPy, pandas, PyTorch).
  • Deep ML expertise: Excellent knowledge of modern machine learning methods and development best practices, including training strategies, model validation, performance visualization, and experimental design.
  • Deep bioinformatic expertise: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables.
  • Strong knowledge of computational oncology, cancer genomics and analysis of clinicogenomics datasets.
  • Must be authorized to work in the United States

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