Why This Job is Featured on The SaaS Jobs
This post-training research role sits at a pivotal point in the modern SaaS stack: the layer where foundation models are adapted into dependable product capabilities for an API and a flagship application. Rather than focusing on greenfield model pre-training, the remit centers on turning research into deployable improvements that can withstand real-world usage at significant scale.
For a SaaS career, that positioning builds durable leverage. Work that blends reinforcement learning with product constraints tends to sharpen judgment around evaluation design, reliability, and iteration loops that mirror how SaaS teams ship and measure change. Experience collaborating across research and product also maps well to AI-native SaaS organizations where model quality, safety, and efficiency are treated as product features with clear downstream impact.
The role is most aligned with professionals who like operating between experimentation and engineering rigor, and who are comfortable navigating a substantial codebase to diagnose issues end to end. It should suit candidates who prefer research agendas that are accountable to deployment outcomes, and who want their technical contributions to be tested against user-facing requirements rather than benchmark scores alone.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
The Post-Training team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable.
About the Role
As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products.
We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research.
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 and pursue a research agenda to improve model capability and performance.
Collaborate closely with the other research and product teams, allowing customers to optimize their own models.
Build robust evaluations for tracking modeling improvements.
Design, implement, test, and debug code across our research stack.
You might thrive in this role if you:
Have a deep understanding of machine learning and machine learning applications.
Have a working knowledge of relevant models, and building evaluations for model capability improvement.
Are comfortable diving into a large ML codebase to debug.
Thrive in a dynamic and technically complex environment.
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.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
