Staff Inference Software Engineer
Posted Updated
- The Inference team builds and operates CoreWeave’s Kubernetes-native inference platform, powering low-latency, high-throughput AI workloads at massive scale
- The team is responsible for request routing, scheduling, GPU resource management, and system-wide optimizations that drive performance, efficiency, and reliability across real-time inference systems
- As a Staff Software Engineer (IC5) on the Inference team, you will act as a technical leader driving architecture, performance, and reliability across multiple services and teams
- Your day-to-day will involve leading cross-team design initiatives, optimizing inference performance (latency, throughput, and GPU utilization), and improving system reliability at scale
- You will work deeply in distributed systems and Kubernetes-based infrastructure, focusing on areas like scheduling, batching, and memory optimization
- This role requires hands-on technical leadership and the ability to influence engineering direction across the organization
- 8–12+ years of experience building and operating large-scale distributed systems or cloud platforms
- Strong understanding of distributed systems, networking, and performance optimization
- Proven experience leading cross-team technical initiatives impacting multiple services or organizations
- Hands-on experience with inference systems, including batching or micro-batching strategies, caching, and memory optimization
- Deep expertise in Kubernetes at production scale, including orchestration, scheduling, and service design
- Experience improving system performance using metrics-driven approaches (e.g., latency, throughput, utilization)
- Experience designing and operating low-latency, high-throughput systems with strict P95/P99 latency requirements
- Familiarity with mixed precision (BF16, FP8) and streaming inference workloads
- Strong programming skills in Go, Python, or C++
- You’re curious about AI inference, GPU systems, and emerging performance techniques
- We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk
- You’re an expert in building reliable, low-latency infrastructure and driving system-wide improvements
- You love to design and optimize high-performance distributed systems at scale
- Experience with GPU systems and performance optimization (CUDA, NCCL, RDMA, NUMA, GPU interconnects)
- Experience with inference frameworks such as vLLM, Triton, TensorRT-LLM, Ray Serve, or TorchServe
- Exposure to large-scale AI/ML infrastructure or hyperscale cloud environments
- Experience leading multi-team or org-level technical initiatives