Software Engineer, Inference GPU Enablement

About the Team
OpenAI’s Inference team ensures that our most advanced models run efficiently, reliably, and at scale. We build and optimize the systems that power our production APIs, internal research tools, and experimental model deployments. As model architectures and hardware evolve, we’re expanding support for a broader set of compute platforms - for example AMD GPUs - to increase performance, flexibility, and resiliency across our infrastructure.

We are forming a team to generalize our inference stack - including kernels, communication libraries, and serving infrastructure - to alternative hardware architectures like AMD.

About the Role
We’re hiring engineers to scale and optimize OpenAI’s inference infrastructure across emerging GPU platforms. You’ll work across the stack - from low-level kernel performance to high-level distributed execution - and collaborate closely with research, infra, and performance teams to ensure our largest models run smoothly on new hardware.

This is a high-impact opportunity to shape OpenAI’s multi-platform inference capabilities from the ground up.

In this role, you will:

• Design and optimize high-performance GPU kernels for AMD accelerators using HIP, Triton, or other performance-focused frameworks.

• Build and tune collective communication libraries (e.g., RCCL) used to parallelize model execution across many GPUs.

• Integrate internal model-serving infrastructure (e.g., vLLM, Triton) into AMD-backed systems.

• Debug and optimize distributed inference workloads across memory, network, and compute layers.

• Validate correctness, performance, and scalability of model execution on large AMD GPU clusters.
  

You can thrive in this role if you:

• Have experience writing or porting GPU kernels using HIP, CUDA, or Triton, and care deeply about low-level performance.

• Are familiar with communication libraries like NCCL/RCCL and understand their role in high-throughput model serving.

• Have worked on distributed inference systems and are comfortable scaling models across fleets of accelerators.

• Enjoy solving end-to-end performance challenges across hardware, system libraries, and orchestration layers.

• Are excited to be part of a small, fast-moving team building new infrastructure from first principles.
  

Nice to Have:

• Contributions to open-source libraries like RCCL, Triton, or vLLM.

• Experience with GPU performance tools (Nsight, rocprof, perf) and memory/comms profiling.

• Prior experience deploying inference on AMD or other non-NVIDIA GPU environments.

• Knowledge of model/tensor parallelism, mixed precision, and serving 10B+ parameter models.

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 do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.

For US Based Candidates: Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link .

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.