Why This Job is Featured on The SaaS Jobs
This Technical Lead role sits at the intersection of applied research and real-world deployment, an increasingly central seam in modern SaaS as AI capabilities move from cloud-only features to on-device experiences. The focus on selecting silicon platforms and shaping transformer architectures around latency, memory, and power constraints reflects a shift toward productizing advanced models under practical operating limits, not just improving benchmarks.
For a SaaS career, the standout value is the end-to-end exposure to how model capability becomes a shippable system. Work spanning hardware evaluation, inference stack implementation, and performance tradeoff analysis builds a durable toolkit for AI-enabled SaaS: understanding cost and responsiveness drivers, building reliable runtimes, and partnering across research and infrastructure to translate prototypes into repeatable delivery.
This role is best suited to engineers who enjoy operating close to the metal while still influencing higher-level system design decisions. It will fit professionals who are comfortable navigating ambiguity in emerging deployment patterns and who prefer cross-functional collaboration with research and platform stakeholders. It also aligns with candidates motivated by technical leadership that blends hands-on optimization with team-building responsibility.
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 in 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 Technical Lead 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:
Evaluate and select silicon platforms (GPUs, NPUs, and specialized accelerators) for on-device and edge deployment of OpenAI models.
Work closely with research teams to co-design model architectures that meet real-world deployment constraints such as latency, memory, power, and bandwidth.
Analyze and model system performance, identifying tradeoffs between model design, memory hierarchy, compute throughput, and hardware capabilities.
Partner with hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads.
Build and lead a team of engineers responsible for implementing the low-level inference stack, including kernel development and runtime systems.
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 experience evaluating or deploying workloads on GPUs, NPUs, or other specialized accelerators.
Understand the performance characteristics of transformer models, including attention, KV-cache behavior, and memory bandwidth requirements.
Have designed or optimized high-performance compute systems, such as inference engines, distributed runtimes, or hardware-aware ML pipelines.
Have experience building or leading teams working on low-level performance-critical software such as CUDA kernels, compilers, or ML runtimes.
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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