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Remote Biomedical Machine Learning Jobs in Stanford, CA

ServiceNow

Staff Machine Learning Engineer

Santa Clara, CA · On-site +1

$176K - $308K/yr

You will play a major part in building AI and Machine Learning (ML) solutions that transform the ... Work personas (flexible, remote, or required in office) are categories that are assigned to ...

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ServiceNow

Staff Machine Learning Engineer

Santa Clara, CA · On-site +1

$176K - $308K/yr

You will play a major part in building AI and Machine Learning (ML) solutions that transform the ... Work personas (flexible, remote, or required in office) are categories that are assigned to ...

New

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All JobsBiomedical Machine Learning JobsRemote Biomedical Machine Learning JobsRemote Biomedical Machine Learning Jobs in Stanford, CA

Remote Biomedical Machine Learning information

See Stanford, CA salary details

$18

$33

$45

How much do remote biomedical machine learning jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for remote biomedical machine learning in Stanford, CA is $33.52, according to ZipRecruiter salary data. Most workers in this role earn between $28.51 and $37.84 per hour, depending on experience, location, and employer.

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 job categories do people searching Remote Biomedical Machine Learning jobs in Stanford, CA look for?

The top searched job categories for Remote Biomedical Machine Learning jobs in Stanford, CA are:

What cities near Stanford, CA are hiring for Remote Biomedical Machine Learning jobs?

Cities near Stanford, CA with the most Remote Biomedical Machine Learning job openings:

Remote Biomedical Machine Learning jobs near you

Machine Learning Engineer

Uber Technologies, Inc.

San Francisco, CA • On-site, Remote

Full-time

Retirement

Posted 24 days ago

Uber rating

6.7

Company rating: 6.7 out of 10

Based on 116 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire

Job description

About the Role

Uber's newly formed AI Security team, part of the Core Security Engineering organization, is building the foundation for dynamic, data-driven security systems. We're evolving Uber's Zero Trust Architecture (ZTA) to be more risk-adaptive across authentication and authorization, moving beyond static rules and manual approvals toward real-time, ML-driven access decisions that secure both humans and AI agents. 

As an ML Engineer, you'll help translate business and security needs into concrete ML problems, build models and features, and take them into production. You'll be part of a team working on greenfield projects at the intersection of ML, security, and infrastructure, shaping how Uber secures AI at scale.

What the Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

  1. Support framing business and security problems as ML tasks. 
  2. Build and iterate ML models that enable risk-adaptive, real-time decisions. 
  3. Engineer features from Uber's risk systems, logs, and contextual signals. 
  4. Deploy and maintain ML pipelines in production, ensuring reliability and scalability. 
  5. Collaborate with senior engineers to integrate ML into Uber's authentication and authorization systems.


---- Basic Qualifications ----

  1. 3+ years experience building and deploying ML models in production, with hands-on work in feature engineering, training, and evaluation. 
  2. Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar). 
  3. Strong foundation in ML algorithms: tree-based models (XGBoost, LightGBM), classical methods (logistic regression, SVMs), and exposure to neural networks (CNNs, RNNs, Transformers). 
  4. Ability to analyze business/security requirements and support translating them into ML use cases.


---- Preferred Qualifications ----

  1. Experience with risk, fraud, anomaly detection, or security-related ML systems. 
  2. Familiarity with large-scale data/infra systems (Kafka, Hive, Spark, Flink, Pinot). 
  3. Exposure to handling challenges such as imbalanced data, feedback loops, or iterative retraining. 
  4. Strong communication skills and ability to work cross-functionally with infra, risk, and security teams.
~~ ~~

Ready to Ride?


This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.


You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.


Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.


Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

For San Francisco, CA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.


For Seattle, WA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.


For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

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