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Machine Learning Research Manager
Rad AI · San Francisco, California, United States
Pay
$135k–280k
Setting
Remote
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 https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html 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 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html 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 https://www.linkedin.com/company/radai/?utm_campaign=Recruiting_2026&utm_content=recruiting-job-posting-website&utm_source=recru%5B%E2%80%A6%5Db-posting-website 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 http://radai.com or no-reply@ashbyhq.com.
Listed by Rad AI for a position based in the United States. Employers on this board attest they are hiring domestically.
Data Engineer
Rad AI · San Francisco, California, United States
Pay
$145k–200k
Setting
Remote
Data Engineer
Listed by Rad AI for a position based in the United States. Employers on this board attest they are hiring domestically.
Staff Software Engineer, Infrastructure
Rad AI · United States
Pay
$175k–245k
Setting
Remote
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 https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html 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 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html 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
The Platform Engineering organization at Rad AI builds the foundations that power all of our products—Reporting, Impressions, and Continuity—and enables product teams to ship reliably, safely, and at scale. Within Platform, the Infrastructure team owns our core cloud infrastructure, platforms, and reliability practices. We’re hiring a Staff Software Engineer to help us design and operate robust, scalable systems. In this role, you’ll contribute to infrastructure architecture, reliability practices, and thoughtful improvements to our workflows. If you’re passionate about building resilient platforms and enjoy collaborating across functions, we’d love to hear from you.
What You’ll Be Doing:
- Influence the technical direction for infrastructure and platform capabilities that support our rapidly growing AI product suite.
- Architect and evolve our cloud infrastructure (primarily on AWS) across container orchestration (Kubernetes, Elastic Container Service), serverless (e.g., Lambda), virtual machines (e.g., EC2), and data stores to support current and future products.
- Work closely with Platform leadership, product engineering, data, and ML teams to design systems that are robust, observable, and compliant in a healthcare environment.
- Define and drive infrastructure strategy for the Platform org—partnering with engineering leadership to align roadmaps, set standards, and sequence work for maximum business impact.
- Secure networking, identity, and access patterns across environments.
- Improve reliability and operational excellence by defining SLOs, SLIs, and error budgets for core platform services.
- Leading and participating in blameless post-incident reviews and translating learnings into systemic improvements.
- Own observability and monitoring strategy across logging, metrics, and tracing, ensuring we can detect, debug, and prevent issues efficiently.
- Mentor and level up engineers across Platform and product teams—reviewing design docs, guiding architecture decisions, and modeling high standards for reliability, security, and maintainability.
- Partner with security and compliance stakeholders to ensure our infrastructure and operational practices meet HIPAA and other healthcare requirements.
- Advocate for and implement developer experience improvements, such as better CI/CD workflows, faster feedback loops, and tooling that reduces cognitive load for product teams.
Who We’re Looking For
- Bring 8+ years of hands-on infrastructure / platform development experience (or equivalent practical experience) in modern, cloud-native environments, with a track record of owning critical systems in production.
- Have deep expertise with AWS (preferred) and/or GCP, including core networking, compute, storage, and managed services.
- Are highly proficient in at least one programming/scripting language used for infrastructure work (Python preferred).
- Extensive experience building tooling and automation for other engineers.
- Have strong experience with Kubernetes, containers (Docker), and container orchestration, and understand how to operate these systems reliably at scale.
- Are comfortable with Infrastructure as Code (Terraform preferred, Pulumi, or similar) and Git-based workflows.
- Possess solid Linux fundamentals and are comfortable debugging issues at the OS, networking, and application layers.
- Have demonstrable experience leading complex, cross-team initiatives from design through rollout—communicating tradeoffs, aligning stakeholders, de-risking launches, and measuring impact.
- Communicate clearly and empathetically with both technical and non-technical partners, and enjoy mentoring engineers at multiple levels.
- Take a data-informed, pragmatic approach to decision-making—balancing ideal architecture with business needs, delivery timelines, and team capacity.
Nice to Haves
- Experience in regulated environments (e.g., HIPAA) or prior work in healthcare or healthtech.
- Background in platform or security engineering, especially around access control, encryption, auditability, and compliance.
- Experience working closely with ML / data teams or with ML platforms (e.g., Airflow, Ray, ML pipelines, model serving stacks).
- Familiarity with observability stacks (CloudWatch, New Relic, Grafana, OpenTelemetry, etc.).
- Experience designing or operating internal developer platforms, SDKs, or reusable frameworks that standardize how services are built and deployed.
- Prior experience at a fast-growing startup where you’ve helped scale infrastructure, processes, and teams.
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 https://www.linkedin.com/company/radai/?utm_campaign=Recruiting_2026&utm_content=recruiting-job-posting-website&utm_source=recru%5B%E2%80%A6%5Db-posting-website 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 http://radai.com or no-reply@ashbyhq.com.
Listed by Rad AI for a position based in the United States. Employers on this board attest they are hiring domestically.
Staff ML Research Scientist
Rad AI · San Francisco, California, United States
Pay
$190k–260k
Setting
Remote
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 https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html 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 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html 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.
What You'll Do:
- 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.
We welcome applicants from across the United States, with a preference for this role to be based in our new San Francisco office.
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 https://www.linkedin.com/company/radai/?utm_campaign=Recruiting_2026&utm_content=recruiting-job-posting-website&utm_source=recru%5B%E2%80%A6%5Db-posting-website 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 http://radai.com or no-reply@ashbyhq.com.
Listed by Rad AI for a position based in the United States. Employers on this board attest they are hiring domestically.
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