TL;DR

Inference Technical Lead (AI): Evaluating and selecting silicon platforms for on-device deployment of OpenAI models with an accent on model architectures, latency, memory, power, and bandwidth. Focus on hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads.

Location: 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.

Salary: $445K + Offers Equity

Company

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

What you will do

  • 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.
  • Take nascent research capabilities and turn them into capabilities we can build on top of.

Requirements

  • 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.

Culture & Benefits

  • We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products.
  • 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.
  • We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.