Production-Grade LLM Inference Runtime Engineer

AI Chopping Block; San Francisco, Northern (CA, KY); Hybrid; USD 250,000 - 360,000; Full time

Job summary

OpenAI is seeking a systems-focused engineer to design and implement the LLM inference runtime for frontier models on our custom silicon. You'll bridge model execution with the hardware, shaping how workloads map onto the platform and how production workloads achieve high throughput and low latency.

You will collaborate across model, systems, compiler, kernel, and hardware teams to build a scalable, observable runtime and to deliver reliable, production-grade performance on OpenAI's AI

Qualifications

• Strong systems programming experience in C++, Rust, Python, or comparable performance-oriented environments.
• Experience building or optimizing runtimes, distributed systems, or model-serving infrastructure.
• Understanding of modern LLM inference including batching, prefill/decode behavior, and model parallelism.
• Ability to reason about latency, throughput, memory bandwidth, and utilization.
• Experience profiling and debugging across hardware-software stacks.
• Able to design clean abstractions with low-level control to extract performance from specialized hardware.

Responsibilities

• Design and implement the LLM inference runtime for frontier models running on custom silicon.
• Build scheduling, continuous batching, memory management, KV-cache management, and execution orchestration for high-performance inference.
• Develop distributed execution strategies across chips, hosts, and racks, including model partitioning, communication, and synchronization.
• Optimize end-to-end latency, throughput, memory efficiency, and hardware utilization across diverse model architectures and serving workloads.
• Partner with kernel, compiler, architecture, and silicon teams to co-design interfaces and remove performance bottlenecks across the stack.
• Enable new model features, execution patterns, numerical formats, and hardware capabilities in a reliable production runtime.
• Create profiling, observability, benchmarking, and performance-modeling tools that make runtime behavior measurable and actionable.
• Debug complex correctness, performance, and reliability issues spanning model code, runtime software, communication layers, and hardware.
• Turn workload insights into clear requirements for future generations of silicon and system architecture.

Skills

C++

Rust

Python

Distributed systems

Systems programming

Performance optimization

Job description

OpenAI is seeking a systems-focused engineer to design and implement the LLM inference runtime for frontier models on our custom silicon. You'll bridge model execution with the hardware, shaping how workloads map onto the platform and how production workloads achieve high throughput and low latency.

You will collaborate across model, systems, compiler, kernel, and hardware teams to build a scalable, observable runtime and to deliver reliable, production-grade performance on OpenAI's AI