over 1 year ago
Base Salary
$295k - $555k/yr
Responsibilities
- Bring new AI technologies into production alongside machine learning researchers, engineers, and product managers.
- Enable advanced research through engineering support.
- Introduce techniques, tools, and architecture to improve inference performance, latency, throughput, and efficiency.
- Build visibility tools for identifying bottlenecks and instability, then implement solutions for priority issues.
- Optimize code and Azure VM fleets for efficient GPU hardware utilization.
Requirements
- At least five years of professional software engineering experience.
- Understanding of modern machine learning architectures and inference performance optimization.
- Familiarity with PyTorch, NVIDIA GPUs, NCCL, CUDA, InfiniBand, MPI, and NVLink, or the ability to gain that familiarity quickly.
- Experience architecting, building, observing, and debugging production distributed systems.
- Experience rebuilding or substantially refactoring production systems as scale increases.
- Ability to own problems end-to-end, work independently, and identify high-priority problems.
- Collaborative, humble, and team-oriented attitude.
Categories
About OpenAI
OpenAI builds and deploys large-scale AI models and tools—including ChatGPT, GPT-4–class models, DALL·E, and Whisper—sold via APIs and enterprise subscriptions to developers and businesses. It monetizes through usage-based API pricing and ChatGPT Plus/Team/Enterprise, and also reaches customers via Microsoft’s Azure OpenAI Service. Founded in 2015 and headquartered in San Francisco, it operates as a private partnership.