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Machine Learning Research Analyst Jobs in California

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct research to optimize performance on Sohu, collaborating with hardware architects to develop software solutions that leverage the unique ...

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct novel research to achieve results on Sohu, translating core mathematical operations into performant instruction sequences and ...

Machine Learning Engineer

San Mateo, CA · On-site

$110K - $165K/yr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Machine Learning Research Engineer

Emeryville, CA · On-site +1

$237K/yr

We're looking for an experienced Machine Learning Engineer to build and improve the models and ML ... Partner with ML and protein design scientists to prototype research ideas and bring them into ...

Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning research. Minimum Qualifications: • Master's degree ...

Machine Learning Researcher

San Diego, CA · On-site

$159K - $238K/yr

Applies Machine Learning knowledge to conduct fundamental research to create new models or training methods in various technology areas (e.g., deep generative models, Bayesian deep learning ...

Showing results 21-40

Machine Learning Research Analyst information

What does a machine learning research analyst do?

A Machine Learning Research Analyst studies and develops algorithms that enable computers to learn from data. They analyze large datasets, experiment with different machine learning models, and evaluate their performance to solve complex problems. Their work often involves staying updated with the latest research in artificial intelligence and applying these advancements to real-world applications. The role typically requires strong programming, statistical, and problem-solving skills.

How does a machine learning research analyst typically collaborate with data scientists and engineers during a project?

As a Machine Learning Research Analyst, you’ll often work closely with data scientists to interpret complex data sets, develop hypotheses, and validate models. Collaboration with engineers is essential to ensure that research findings are correctly implemented into production systems. Regular meetings, code reviews, and joint problem-solving sessions are common, allowing you to provide analytical insights while engineers focus on system scalability and deployment. This teamwork helps bridge the gap between theoretical research and practical application, leading to impactful solutions.

What are the key skills and qualifications needed to thrive as a machine learning research analyst, and why are they important?

To thrive as a Machine Learning Research Analyst, you need a solid background in mathematics, statistics, and computer science, often demonstrated by a relevant degree or research experience. Proficiency with programming languages like Python or R, familiarity with machine learning libraries (such as TensorFlow or PyTorch), and experience with data analysis tools are typically required. Strong analytical thinking, creativity, and effective communication skills help distinguish top performers in this role. These capabilities enable analysts to develop innovative models, interpret complex data, and clearly present actionable insights to stakeholders.

What is the difference between Machine Learning Research Analyst vs Data Scientist?

AspectMachine Learning Research AnalystData Scientist
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of ML algorithmsBachelor's or Master's in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentResearch labs, academic institutions, tech companies focusing on ML innovationsBusiness environments, analytics teams, tech companies applying data insights
Employer & Industry UsageResearch institutions, AI startups, tech giants focusing on ML advancementsCorporate, finance, healthcare, and e-commerce sectors leveraging data for decision-making

While both roles require strong analytical skills and knowledge of machine learning, Machine Learning Research Analysts focus more on developing and testing new algorithms in research settings. Data Scientists apply these techniques to solve practical business problems, often working directly with large datasets to generate insights and support decision-making.

What cities in California are hiring for Machine Learning Research Analyst jobs?

Cities in California with the most Machine Learning Research Analyst job openings:

Infographic showing various Machine Learning Research Analyst job openings in California as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Research Manager

San Francisco, CA • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


Job description

About Rad AI

At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI‑driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.

Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting‑edge AI.

Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one‑third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.

Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked by Deloitte as the 19th fastest‑growing company in North America, we are building AI‑powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 list, highlighting the innovation and momentum behind our mission.

If you’re ready to shape the future of healthcare, we’d love to have you on our team!

Why Join Us?

We’re looking for a Machine Learning Research Manager to lead a dedicated, high‑impact team of applied and clinical researchers working at the intersection of clinical AI, language modeling, and radiology.

This is a player‑coach role for someone who loves developing people, setting technical direction, and staying hands on and being close to the work. You’ll help shape how our research organization scales while partnering deeply with clinicians, engineers, and product leaders to bring high‑value ideas into production.

What You’ll Be Doing
  • Directly manage and mentor a small team of applied and clinical researchers, helping them grow in scope, judgment, execution, and communication
  • Drive research productivity by clarifying priorities, unblocking work, and creating a high‑trust, high‑accountability team environment
  • Stay close to the technical work as a player‑coach by guiding problem framing, experimental design, evaluation strategy, and tradeoff decisions across multiple research efforts
  • Partner closely with radiologists, clinical experts, engineers, and product leaders to identify the highest‑leverage research opportunities and translate them into production‑scale systems
  • Help the team build and evaluate advanced NLP and reasoning systems that work with clinical text, diagnostic criteria, reporting workflows, and other healthcare data
  • Create strong cross‑functional working rhythms with engineering, product, and clinical partners so research outputs are practical, trustworthy, and deployable
  • Raise the bar on research quality, reproducibility, and communication across the team
  • Stay current on relevant machine learning advances and help the team thoughtfully integrate new methods when they materially improve customer and clinical outcomes
Who We’re Looking For
  • MS or PhD in Computer Science, Machine Learning, Computational Linguistics, Biomedical Informatics, or a related quantitative field, or equivalent practical experience
  • 6+ years of applied ML research experience, with a track record of taking work from idea to production impact
  • Prior people management experience, or clear evidence of operating as a de facto team lead for multi‑person research efforts, with strong coaching and prioritization skills
  • Strong background in NLP and modern deep learning, especially transformer‑based systems and large language models
  • Experience applying ML to hard real‑world problems where ambiguity, data quality, and operational constraints matter
  • Strong hands‑on experience with modern ML tooling such as PyTorch and common model development workflows
  • Demonstrated ability to collaborate closely with domain experts and cross‑functional stakeholders, especially in environments where trust, iteration speed, and communication quality matter
  • Excellent written and verbal communication skills, with the ability to guide senior researchers while also aligning non‑technical partners around research direction and tradeoffs
Nice to Have
  • Experience working in healthcare, clinical AI, biomedical ML, or other regulated, privacy‑sensitive environments
  • Experience with radiology, clinical documentation, medical terminology, or clinician‑facing workflows
  • Experience deploying LLM or NLP systems in production settings
  • Experience contributing to research culture through mentorship, technical standards, or organizational leadership
  • Familiarity with cloud‑based ML workflows and modern research infrastructure
  • Preferably eager to collaborate and work in our new San Francisco office and shape the culture and tone of that space

Join our world‑class team as we build and deploy AI solutions that empower physicians and transform patient care—making a meaningful impact on millions of lives. Driven by our mission, we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you!

To learn more about what it's like to work at Rad AI, visit https://www.radai.com/life-at-rad-ai and be sure to follow us on LinkedIn to stay up to date!

For US‑Based Full‑Time Roles, Rad AI offers a variety of benefits, including:

  • Comprehensive Medical, Dental, Vision & Life insurance
  • HSA (with employer match), FSA, & DCFSA
  • 401(k)
  • 11 Paid Company Holidays
  • Flexible PTO policy
  • Annual company‑wide offsite
  • Periodic team offsites
  • Annual equipment stipend
  • For roles based outside the US, your recruiter can share more details

At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @radai.com or no‑reply@ashbyhq.com.

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