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San Francisco, California, United States
Hybrid
About the Team
The Health team, within OpenAI’s broader Personal AGI organization, has a mission to ensure AGI improves health for all humanity.
Improving human health will be one of the defining impacts of AGI. Hundreds of millions of people already turn to ChatGPT for questions about their health and millions of clinicians use it weekly to support care delivery. Increasingly capable models create an opportunity to make high-quality medical intelligence more accessible across patients and clinicians—raising the floor of human health—and accelerate the new capabilities and scientific advances that raise the ceiling of human health.
Our job is to make those benefits real. We work across the full model stack—pretraining, midtraining, reinforcement learning, post-training, evaluations, harnessing, and deployment—and connect that research to the patients, clinicians, and real-world outcomes we aim to improve.
About the Role
We’re looking for an exceptional, hands-on researcher who wants to build frontier health capabilities and turn them into impact at scale. This is a role for someone who can take an important, underdefined problem from 0→1: identify the right bet, build what’s needed to test it, and drive it all the way to a measurable improvement in the models and products we actually ship.
We’re especially excited about two kinds of people: researchers with the technical depth to move the frontier in pretraining, reinforcement learning (RL) / post-training, or evals; and researchers with real depth in developing frontier biomedical AI capabilities. Prior experience in healthcare is helpful but not required. Research excellence, velocity, ownership, and alignment with the mission are most important to us.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Own a high-leverage research direction end to end—from deciding which problem matters and how to measure it, to designing and running experiments, to integrating successful work into frontier models.
Develop scalable methods across pretraining, midtraining, reinforcement learning, and post-training to improve health reasoning, knowledge, reliability, calibration, and behavior.
Build and study RL environments grounded in real health problems; understand which data and training setups produce robust, generalizable improvements rather than just higher benchmark scores.
Create meaningful, trustworthy, and unsaturated evaluations that tell us whether our models are actually getting better at what matters for patients and clinicians.
Advance new 0→1 capabilities in health that may have an increasing impact with upcoming increases in model intelligence and test-time compute.
Develop models and agents that can work over longitudinal, multimodal health data to produce useful predictions, surface new scientific insights, and support better individual- and population-level decisions.
Work closely with researchers, engineers, clinicians, and product teams to bring health capabilities into the models and products used by hundreds of millions of people.
Help establish that AI improves real health outcomes, not just that it can produce impressive answers or demos.
You might thrive in this role if you:
Care deeply about using increasingly capable AI to improve human health, and take seriously the responsibility of deploying it safely.
Have an unusually strong track record in machine learning or AI research, with the depth to push at least one important area forward: pretraining, reinforcement learning / post-training, evals (not necessarily specific to health); or substantial depth in a relevant frontier health / biomedical AI problem.
Are a hands-on builder: you can design experiments, write and debug code, work directly with data and training infrastructure, and move quickly from an idea to evidence.
Have strong research taste and can distinguish an important problem or a promising approach from an interesting one.
Own ambiguous problems end to end, and are willing to learn whatever is missing to get the job done.
Stay goal-oriented rather than method-oriented, and don’t shy away from unglamorous work if it is the highest-leverage path to impact.
Care about whether a capability will scale, generalize, and make it into the real world—not just whether it can be shown in a paper or prototype.
Enjoy working with low-ego, ambitious people across research, engineering, medicine, and product.
Bonus: Experience with health AI, longitudinal health data, or clinical research.
If you want your work to help make medical intelligence widely accessible—and to work on some of the most important frontier problems at the intersection of AI, science, and human health—we’d love to hear from you.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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