Operating Systems Engineer, On-Device Inference | Consumer Devices

ABOUT THE TEAM

OpenAI Consumer Devices is building the next generation of products that bring powerful AI into people’s everyday lives. Guided by OpenAI’s mission to ensure AGI benefits all of humanity, our team combines world-class researchers, engineers, designers, and operators who care deeply about creating useful, intuitive, and responsible technology. You’ll have the opportunity to work alongside exceptional people on ambitious, zero-to-one challenges at the intersection of hardware, software, and AI. This is a chance to help define an entirely new category of products—and shape how people experience AI in the future.

Our team works across silicon, embedded systems, operating systems, and cloud services to build reliable consumer devices and the novel platforms required to support them. We partner closely with research to bring advanced AI capabilities into the physical world.

ABOUT THE ROLE

As an Operating Systems Engineer focused on on-device inference, you will design, develop, and ship the OS stack that makes advanced AI capabilities reliable, responsive, and energy efficient on consumer devices.

Your work will span OS services and frameworks, inference runtime integration, model fitting, scheduling, and performance and power management. You’ll partner with research to adapt models to device constraints, make design decisions across the stack, and carry solutions from early exploration through integration and production.

IN THIS ROLE, YOU WILL:

- Build the inference platform: Design and implement maintainable OS services, frameworks, and clear interfaces for inference execution, model loading and lifecycle, and resource management.

- Fit models to device constraints: Partner with researchers on quantization, runtime integration, and memory optimization to meet memory, compute, and energy budgets while evaluating model quality and product behavior.

- Coordinate system resources: Develop scheduling and resource policies that balance inference with other device activity, preserving responsiveness within latency, memory, battery, and thermal constraints.

- Advance performance and power management: Develop and validate execution strategies that adapt to workload needs, available resources, and changing device conditions.

- Debug across the stack: Use tracing, profiling, and structured debugging to investigate correctness, concurrency, performance, and reliability issues across models, inference runtimes, and OS components.

- Measure and validate improvements: Build diagnostic tools, instrumentation, representative device workloads, and automated tests to demonstrate repeatable performance and energy gains on physical devices, catch regressions, and validate sustained use.

- Bring capabilities to production: Collaborate with research, hardware, firmware, platform, and product engineering teams to turn emerging model capabilities into maintainable systems and reliable shipped features.

MINIMUM QUALIFICATIONS

- Substantial hands-on experience designing, developing, and debugging operating system components, system services, or performance-critical platform software.

- Proficiency in C++ for systems development, including concurrent programming, memory ownership, and resource lifetime management.

- Hands-on experience integrating or optimizing inference runtimes or machine learning workloads in resource-constrained environments.

- Strong understanding of scheduling, memory management, and how workloads compete for shared system resources.

- Experience diagnosing complex system behavior and delivering performance or power improvements supported by repeatable measurements.

- Ability to work across disciplines, translate research and product needs into system requirements, and explain technical decisions and tradeoffs clearly.

YOU MIGHT THRIVE IN THIS ROLE IF YOU:

- Have delivered end-to-end on-device inference in shipped products, from model adaptation and runtime integration through OS suppo …