Why This Job is Featured on The SaaS Jobs
Work on on-device transformer models sits at an increasingly important intersection for SaaS: cloud-scale foundation model research meeting real product constraints at the edge. This listing is notable because it centers the practical problem of making multimodal models usable on consumer devices, where latency, power, and memory ceilings force different tradeoffs than typical server-side inference.
For a SaaS career, this kind of role builds durable leverage in model evaluation, architecture iteration, and performance-aware experimentation that translates across AI-native products. The emphasis on turning “nascent research capabilities” into something teams can build on mirrors a common SaaS inflection point: moving from demos to repeatable capabilities that can be shipped, monitored, and improved. Collaboration with researchers and design partners also reflects how modern SaaS AI features are shaped by both technical feasibility and product experience.
This position tends to suit professionals who enjoy rigorous, evidence-driven iteration and are motivated by constraints rather than unlimited scaling. It will likely appeal to those who want to stay close to research while still orienting work toward deployable outcomes, especially in hybrid environments where cross-functional decision-making happens in person.
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 Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models to support our vision as we advance forward in our mission of building AGI that benefits all of humanity.
About the Role
As a Research Engineer/Scientist on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities.
This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees.
In this role you will:
Train and evaluate multimodal SoTA models along axis that are important to our vision for future devices.
Develop novel architectures that improve model performance when scaling the models themselves is not an option.
Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of.
You might thrive in this role if you:
Have a research background related to developing on-device transformer models.
Love performance optimization and working with GPU kernel engineers (but you do not need CUDA experience yourself).
Do rigorous science (rather than vibes based). We need confidence in the experiments we run to move quickly.
Have already spent time in the weeds teaching models to speak and perceive.
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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