Senior Level Machine Learning Research Jobs
Senior level machine learning research jobs place experienced researchers at the helm of defining research agendas, owning experimental outcomes, and leading the cross-functional teams that translate breakthroughs into production systems. Openings concentrate across Biotechnology & Pharmaceuticals, Medical Devices, and Electronics & Hardware, with a mix of on-site, hybrid, and remote roles, and employers like Rad AI, Apple, and Jane Street hiring at this level now.
Find JobsOverview
Showing 5 of 7+ Senior Level Machine Learning Research jobs
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 Staff Machine Learning Research Scientist to help define and drive Rad AI's next generation of applied research in NLP and clinical AI. We work across LLMs, retrieval, representation learning, speech and multimodal modeling, and we care as much about evaluation and reliability as we do about state-of-the-art results. You will have scope, ownership, and a direct line from research to product. You'll collaborate closely with clinicians, engineers, and product leaders to translate foundational research into production-scale systems that improve outcomes for doctors and patients alike. As we grow, you will help shape standards for model quality, safety, and observability, and contribute to strategic initiatives that include computer vision and vision-language work.
- Own end-to-end applied research: frame the problem, design experiments, ship to production, and monitor impact against real-world metrics.
- Set technical direction across LLMs, retrieval, and multimodal; run ablations/error analysis that change product decisions.
- Build evaluation that matters: link offline metrics to online outcomes; define thresholds, monitoring, and rollback.
- Partner to deliver with engineering and product—and, when relevant, clinicians/domain experts—to align data, success criteria, and timelines.
- Raise the bar by mentoring peers and codifying standards for reliability, safety, and documentation.
- Improve the platform (data, training, serving, observability) to speed iteration and ensure reproducibility.
- Explore new directions, with computer vision/vision-language work as a nice-to-have for future strategic initiatives.
What We're Looking For
- MS or PhD (or equivalent research experience) in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or related quantitative field.
- 7+ years of applied ML research experience (or PhD + 5 years, or equivalent evidence of Staff-level impact).
- Depth in one or more areas: LLMs and NLP, computer vision, speech, recommendation/ranking, retrieval, or multimodal modeling.
- Strong experimental rigor: clear hypothesis framing, offline→online linkage, calibration and stratified analyses, ablations that influence decisions.
- Proven ability to take models to production.
- Hands-on with modern tooling: PyTorch and common experiment/ops tools (for example MLflow, Databricks, Ray, or similar).
- System thinking: can choose methods based on constraints, design for observability and rollback, and document decisions clearly.
- Collaborative communicator who writes crisp design docs and explains complex ideas to non-specialists; comfortable mentoring peers.
Preferred Qualifications
- Health data familiarity, including EHR or imaging.
- Experience in one or more areas: clinical NLP or LLMs, computer vision, speech, retrieval or multimodal modeling.
- Shipped, measured models in production with monitoring and clear rollback; external or multi-site validation is a plus.
- Workflow integration with EHR, RIS, PACS, or reporting systems; PowerScribe or Dragon exposure helpful.
- Strong evaluation practices: calibration, slice analysis, and ablations.
- Safety and governance in sensitive domains, including PHI handling and HIPAA or FDA-adjacent environments.
- Technical mentorship and contributions to team research culture; publications or impactful open-source work.
- Practical tooling: PyTorch plus modern ML ops tools such as MLflow, Databricks, Ray, or Triton.
Why This Matters
Radiologists are the invisible backbone of modern medicine. Every diagnosis, every surgery, every treatment plan begins with their interpretations. Yet they're often overwhelmed by cognitive load, repetitive tasks, and administrative overhead. At Rad AI, we're using ML to change that—building intelligent systems that understand medical context, streamline documentation, and amplify human expertise. You've already seen how AI can transform healthcare. Now help us push it further. Join us in shaping how AI supports the next generation of medical professionals. 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!
Location Details:
For Roles Listed As San Francisco - Onsite
This role will be based in our San Francisco office and we expect employees to work onsite four days per week. The remaining time may be worked remotely or onsite, depending on team and business needs.
For Roles Listed As United States - Remote
This role is open to candidates located anywhere in the United States.
For roles listed as San Francisco - Onsite + United States - Remote:
We will prioritize candidates who can work onsite four days per week in San Francisco, while also considering remote candidates located anywhere in the United States.
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.
Compensation Range: $190K - $260K
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 Staff Machine Learning Research Scientist to help define and drive Rad AI's next generation of applied research in NLP and clinical AI. We work across LLMs, retrieval, representation learning, speech and multimodal modeling, and we care as much about evaluation and reliability as we do about state-of-the-art results. You will have scope, ownership, and a direct line from research to product. You'll collaborate closely with clinicians, engineers, and product leaders to translate foundational research into production-scale systems that improve outcomes for doctors and patients alike. As we grow, you will help shape standards for model quality, safety, and observability, and contribute to strategic initiatives that include computer vision and vision-language work.
- Own end-to-end applied research: frame the problem, design experiments, ship to production, and monitor impact against real-world metrics.
- Set technical direction across LLMs, retrieval, and multimodal; run ablations/error analysis that change product decisions.
- Build evaluation that matters: link offline metrics to online outcomes; define thresholds, monitoring, and rollback.
- Partner to deliver with engineering and product—and, when relevant, clinicians/domain experts—to align data, success criteria, and timelines.
- Raise the bar by mentoring peers and codifying standards for reliability, safety, and documentation.
- Improve the platform (data, training, serving, observability) to speed iteration and ensure reproducibility.
- Explore new directions, with computer vision/vision-language work as a nice-to-have for future strategic initiatives.
What We're Looking For
- MS or PhD (or equivalent research experience) in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or related quantitative field.
- 7+ years of applied ML research experience (or PhD + 5 years, or equivalent evidence of Staff-level impact).
- Depth in one or more areas: LLMs and NLP, computer vision, speech, recommendation/ranking, retrieval, or multimodal modeling.
- Strong experimental rigor: clear hypothesis framing, offline→online linkage, calibration and stratified analyses, ablations that influence decisions.
- Proven ability to take models to production.
- Hands-on with modern tooling: PyTorch and common experiment/ops tools (for example MLflow, Databricks, Ray, or similar).
- System thinking: can choose methods based on constraints, design for observability and rollback, and document decisions clearly.
- Collaborative communicator who writes crisp design docs and explains complex ideas to non-specialists; comfortable mentoring peers.
Preferred Qualifications
- Health data familiarity, including EHR or imaging.
- Experience in one or more areas: clinical NLP or LLMs, computer vision, speech, retrieval or multimodal modeling.
- Shipped, measured models in production with monitoring and clear rollback; external or multi-site validation is a plus.
- Workflow integration with EHR, RIS, PACS, or reporting systems; PowerScribe or Dragon exposure helpful.
- Strong evaluation practices: calibration, slice analysis, and ablations.
- Safety and governance in sensitive domains, including PHI handling and HIPAA or FDA-adjacent environments.
- Technical mentorship and contributions to team research culture; publications or impactful open-source work.
- Practical tooling: PyTorch plus modern ML ops tools such as MLflow, Databricks, Ray, or Triton.
Why This Matters
Radiologists are the invisible backbone of modern medicine. Every diagnosis, every surgery, every treatment plan begins with their interpretations. Yet they're often overwhelmed by cognitive load, repetitive tasks, and administrative overhead. At Rad AI, we're using ML to change that—building intelligent systems that understand medical context, streamline documentation, and amplify human expertise. You've already seen how AI can transform healthcare. Now help us push it further. Join us in shaping how AI supports the next generation of medical professionals. 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!
Location Details:
For Roles Listed As San Francisco - Onsite
This role will be based in our San Francisco office and we expect employees to work onsite four days per week. The remaining time may be worked remotely or onsite, depending on team and business needs.
For Roles Listed As United States - Remote
This role is open to candidates located anywhere in the United States.
For roles listed as San Francisco - Onsite + United States - Remote:
We will prioritize candidates who can work onsite four days per week in San Francisco, while also considering remote candidates located anywhere in the United States.
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.
Compensation Range: $190K - $260K
See All 7 Senior Level Machine Learning Research Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsSenior Level Machine Learning Research Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Medical Devices
- Electronics & Hardware
- Investment & Asset Management
Senior Level Machine Learning Research Jobs: Frequently Asked Questions
How do I get a senior level machine learning research job?
Employers at this level look for candidates who have independently driven research projects from hypothesis through publication or deployment, not just contributed to them. A strong portfolio of first-author work, demonstrated ability to set a research direction, and experience mentoring junior researchers or collaborating across engineering and product teams distinguishes competitive candidates from strong individual contributors.
Which companies hire senior level machine learning researchs?
Companies hiring senior level machine learning researchs right now include Rad AI, Apple, and Jane Street, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a wide range of organizations, including hyperscalers building foundational model infrastructure, enterprise software companies embedding AI into core products, and specialized research labs focused on a single application domain.
Are there remote senior level machine learning research jobs?
Yes, though availability varies by employer and the nature of the research. About 29% of senior level machine learning research openings are remote or hybrid as of November 2026, reflecting how much applied and theoretical research can be conducted without a fixed lab setting. Roles that require specialized on-site compute hardware or close collaboration with hardware teams tend to be more office-dependent.
What makes a machine learning research role senior level?
Senior level machine learning research roles are defined by ownership and scope rather than task execution. Researchers at this stage set the technical direction for a project or domain area, make independent decisions about methodology and experimental design, and are accountable for delivering publishable or deployable results. They are also expected to mentor junior researchers, influence hiring, and contribute to shaping the team's broader research strategy.
Which industries hire the most senior level machine learning researchs?
Senior Level machine learning research roles concentrate in Biotechnology & Pharmaceuticals, Medical Devices, and Electronics & Hardware, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they have both the computational resources to support serious research programs and the business incentive to translate research advances directly into product or platform differentiation.