ML Research Engineer - Hardware Codesign

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We’re seeking a Research-Hardware Codesign Engineer to operate at the boundary between model research and silicon/system architecture. You’ll help shape the numerics, architecture, and technology bets of future OpenAI silicon in collaboration with both Research and Hardware. Your work will include debugging gaps between rooflines and reality, writing quantization kernels, derisking numerics via model evals, quantifying system architecture tradeoffs, and implementing novel numeric RTL. This is a hands-on role for people who go looking for hard problems, get to ground truth, and drive it to production. Strong prioritization and clear, honest communication are essential. Location: San Francisco, CA (Hybrid: 3 days/week onsite). Relocation assistance available. You Will Thrive in this Role if: An exceptional track record of high-quality technical output, and a bias for shipping a prototype now and iterating later in the absence of clear requirements. Strong Python, and C++ or Rust, with a cautious attitude toward correctness and an intuition for clean extensibility. Experience writing Triton, CUDA, or similar, and an understanding of the resulting mapping of tensor ops to functional units. Working knowledge of PyTorch or JAX; experience in large ML codebases is a plus. Practical understanding of floating point numerics, the ML tradeoffs of reduced precision, and the current state of the art in model quantization. Deep understanding of transformer models, and strong intuition for transformer rooflines and the tradeoffs of sharded training and inference in large-scale ML systems. Experience writing RTL (especially for floating point logic) and understanding of PPA tradeoffs is a plus. Strong cross-functional communication (e.g. across ML researchers and hardware engineers); ability to slice ambiguous early-incubation ideas into concrete arenas in which progress can be made. 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. 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