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Remote Bioinformatics Machine Learning Jobs in California

We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning. This is a rare opportunity to tackle open-ended ...

Senior Machine Learning Scientist

Brisbane, CA · On-site +1

$110.10K - $150.40K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... Experience in NGS data analysis and bioinformatic pipelines. * Experience with containerized cloud ...

Senior Machine Learning Scientist

Brisbane, CA · On-site +1

$110.10K - $150.50K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... Experience in NGS data analysis and bioinformatic pipelines. * Experience with containerized cloud ...

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199.68K - $283.50K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... Experience in NGS data analysis and bioinformatic pipelines. * Experience with containerized cloud ...

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199.68K - $283.50K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... Experience in NGS data analysis and bioinformatic pipelines. * Experience with containerized cloud ...

Machine Learning Scientist

Emeryville, CA · On-site +1

$180K - $250K/yr

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into ... Previous experience in data extraction and curation from bioinformatics data sources * Familiarity ...

... Experiences in machine learning and AI • Capability of integrating multiple resources to ... Open to remote candidates if they meet all the required skills and experience and are right fit for ...

Remote Commitment: 5-10 hours per week (flexible) Duration: 3-6 months (with potential extension ... Role Overview We are seeking a Machine Learning Engineer (Volunteer) to help design, build, and ...

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Remote Bioinformatics Machine Learning information

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

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is a Remote Bioinformatics Machine Learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in California? The most popular types of Bioinformatics Machine Learning jobs in California are:
What are popular job titles related to Remote Bioinformatics Machine Learning jobs in California? For Remote Bioinformatics Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Bioinformatics Machine Learning jobs in California look for? The top searched job categories for Remote Bioinformatics Machine Learning jobs in California are:
What cities in California are hiring for Remote Bioinformatics Machine Learning jobs? Cities in California with the most Remote Bioinformatics Machine Learning job openings:
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Posted 28 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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