Software Engineer, Model Inference
About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before.
What this role actually needs.
About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. Responsibilities: - Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. - Work alongside researchers to enable advanced research through awesome engineering. - Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. - Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. - Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. - Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Software Engineer, Model Inference role.
- Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production.
- Work alongside researchers to enable advanced research through awesome engineering.
- Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack.
- Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.
- Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware.
- Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference.
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Source: jobs.ashbyhq.com · Source ID: 83b6755d-7785-4186-9050-5ef3ad127941 · Confidence: 97/100 · Last checked: May 7, 2026
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