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Software Engineer, Workload Enablement

OpenAI · Scaling

Location
San Francisco, California, United States · Seattle, Washington, United States · Remote
Metro
San Francisco Bay Area, Seattle
Workplace
Hybrid
Level
Unspecified
Type
Full-time
Pay
$293K–$385K/yr (published by employer)
Posted
7 months ago
Source
Ashby

Read the full posting & apply ↗

PythonC++KubernetesPyTorchCUDALLMs

What the posting covers

About the Team

The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking,…

About the Role

We’re hiring an SW Engineer to enable production workloads and end-to-end testing on new platforms. This role will include creating new test harnesses and platform stress benchmarks, porting existing inference and training workloads to new, sometimes…

Key Responsibilities

Port and validate key inference and training workloads on new platforms/SKUs as they arrive; drive correctness, performance, and stability to an internal readiness bar. Build a suite of benchmarks and stress tests that capture real E2E behavior of our…

Qualifications

BS in CS/EE (or equivalent practical experience). 5+ years in one or more of: ML systems, performance engineering, distributed systems, or HPC. Strong hands-on experience with: PyTorch and modern LLM training/inference stacks Large-scale distributed training…

Preferred Skills

Experience building workload-shaped benchmarks and stress/fault tests that correlate to production behavior (not just synthetic loops or microbenchmarks). Familiarity with RDMA networking and transport tuning; understanding of how network topology and…

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…