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Remote Biomedical Machine Learning Jobs in California

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Remote Biomedical Machine Learning information

What is a remote biomedical machine learning job?

Remote biomedical machine learning jobs involve applying machine learning and artificial intelligence techniques to biomedical data, such as medical images, genetic information, or clinical records, while working from a remote location. Professionals in these roles develop algorithms to assist in disease diagnosis, drug discovery, or patient outcome prediction. These jobs typically require strong programming skills, experience with data science tools, and a background in biomedical sciences or related fields. Remote positions offer flexibility and the ability to collaborate with interdisciplinary teams from anywhere in the world.

What are some unique challenges faced when working remotely as a biomedical machine learning professional, and how can they be addressed?

Remote Biomedical Machine Learning professionals often face challenges related to accessing large and sensitive datasets, ensuring compliance with data privacy regulations, and maintaining effective communication with interdisciplinary teams such as clinicians and researchers. To address these, it's important to become familiar with secure data transfer protocols, collaborate closely with IT and compliance officers, and utilize robust project management and communication tools. Regular virtual meetings and clear documentation can help bridge gaps and ensure alignment on project goals.

What are the key skills and qualifications needed to thrive as a remote biomedical machine learning specialist, and why are they important?

Thriving in Remote Biomedical Machine Learning requires expertise in machine learning, data analysis, and a strong background in biomedical sciences, often supported by an advanced degree in a related field. Proficiency with programming languages such as Python or R, experience with frameworks like TensorFlow or PyTorch, and familiarity with medical data systems are typically necessary. Excellent problem-solving skills, communication abilities, and self-motivation are standout soft skills for remote collaboration and research. These competencies are vital to effectively develop innovative biomedical solutions, ensure data integrity, and drive impactful research in a distributed work environment.

What is the difference between Remote Biomedical Machine Learning vs Remote Biomedical Data Analyst?

AspectRemote Biomedical Machine LearningRemote Biomedical Data Analyst
Required CredentialsMaster's or PhD in Bioinformatics, Data Science, or related fields; experience with ML frameworksBachelor's or Master's in Biology, Data Analysis, or related; proficiency in data visualization and statistical tools
Work EnvironmentCollaborative remote teams, research labs, tech companiesRemote healthcare organizations, research institutions, biotech firms
Employer & Industry UsageTech companies, biotech startups, research institutionsHospitals, healthcare providers, pharmaceutical companies

Remote Biomedical Machine Learning specialists focus on developing algorithms and models to analyze biomedical data, often requiring advanced degrees and programming skills. In contrast, Remote Biomedical Data Analysts interpret and visualize biomedical datasets, typically with a focus on statistical analysis. Both roles are vital in healthcare and biotech industries but differ in technical depth and responsibilities.

What are the most commonly searched types of Biomedical Machine Learning jobs in California?

The most popular types of Biomedical Machine Learning jobs in California are:

What are popular job titles related to Remote Biomedical Machine Learning jobs in California?

For Remote Biomedical Machine Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Biomedical Machine Learning jobs in California look for?

The top searched job categories for Remote Biomedical Machine Learning jobs in California are:

What cities in California are hiring for Remote Biomedical Machine Learning jobs?

Cities in California with the most Remote Biomedical Machine Learning job openings:

Remote Biomedical Machine Learning jobs near you

Principal, Machine Learning Scientist

BigHat Biosciences

San Mateo, CA • On-site, Remote

$254K - $290K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 20 days ago

Job description

Principal, Machine Learning Scientist
Department: DS/ML (Data Science/Machine Learning)
Employment Type: Full Time
Location: San Mateo, CA
Reporting To: Hunter Elliot
Description
The role: We are seeking a creative, accomplished Principal Machine Learning Scientist to advance the state of the art in ML-driven therapeutic antibody design.
At BigHat Biosciences our full-stack antibody drug development platform uses ML to drive every stage from discovery to optimization. Our roboticized high-throughput wet-lab continually adds to our large proprietary datasets, which are piped through a custom LIMS++ data management and orchestration layer to automatically update and deploy the latest models. This makes the development of complex, next-gen therapeutics 'trivially parallelizable', at a pace which only accelerates as we develop better ML tooling.
You're not interested in just git-cloning the latest NeurIPS pub and swapping out the dataset. Motivated by an enthusiasm for the possibility of addressing unmet patient needs and a curiosity about the underlying biology, you'll apply your world-class ML skillset to refine and expand this state-of-the-art protein engineering platform. Success will mean not only hands-on methods development, but helping shape the direction for future ML research, and actively participating in the application of our platform to the accelerated design of new therapeutics.
Key Responsibilities
  • Design and implement the next state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties, trained on proprietary internal datasets of thousands to millions of antibodies.
  • Provide leadership, technical guidance, and mentorship to other ML and data science FTEs and interns.
  • Help set strategy for future ML research, driven by a strong high-level understanding of BigHat programs and operations as well as real-world drug development challenges.
  • Develop, refine, and deploy de novo design methods for generating initial hits to challenging, therapeutically interesting targets.
  • Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems for validation and deployment in our high-throughput wet lab - at BigHat success is only declared upon synthesis of real antibodies with drug-like properties.
  • Maintain an in-depth understanding of the current state-of-the-art in ML-driven protein engineering, both in the literature and at BigHat.
  • Share your findings at top-tier conferences and publish in leading scientific journals to advance the field of protein engineering.
  • Provide ML expertise and support for ongoing therapeutics programs, directly contributing to the development of new drugs.
  • Collaborate with our engineering team to ensure maximal efficiency in the automated and agentic deployment of our latest models to our therapeutics programs.
  • Work closely with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to identify inefficiencies or potential improvements in BigHat's platform, and plan and prioritize ML methods development accordingly.

Skills Knowledge and Expertise
  • PhD in ML/CS or in the hard sciences with 5+ years experience post-graduation in developing and applying novel ML methods, and a strong quantitative background.
  • Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry.
  • Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices.
  • Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
  • Enjoys a fast-paced environment and excels at executing across multiple projects.
  • Familiarity with the current state-of-the-art in ML-driven protein engineering
  • Nice-to-haves include experience with de novo design, NGS data, Bayesian optimization, familiarity with antibody biology and drug development, and experience training and deploying models on AWS.

Total Rewards
The salary estimated for this position is $254,000 - $290,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer.
What BigHat Offers:
  • Range of health insurance plan options through Anthem and Kaiser (monthly credit if benefit waived)
  • Dental, and vision coverage through Guardian
  • Additional well-being benefits through Nayya, OneMedical, Wagmo, Rula, and more
  • 401(k) with company match
  • DTO, two weeks of company-wide shutdown, and 12 company holidays
  • Paid parental leave

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