Member of Technical Staff - ML Performance

Stack

Responsibilities

• ▹Push language and diffusion models toward higher throughput and lower latency
• ▹Contribute to open-source projects and Modal's container runtime
• ▹Optimize the performance of ML systems at scale

Requirements

• ▹5+ years of experience writing high-quality, high-performance code
• ▹Experience with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT)
• ▹Familiarity with Nvidia GPU architecture and CUDA
• ▹Experience with ML performance engineering (e.g. boosting GPU performance, debugging SM occupancy issues, rewriting algorithms to be compute-bound, eliminating host overhead)

Nice to have

• ▹Familiarity with low-level operating system foundations (Linux kernel, file systems, containers)

Soft skills

About the company

Modal is building the new infrastructure layer for AI, giving customers like Lovable, Ramp, Cognition, DoorDash, and Suno instant GPU access, sub-second container starts, and native storage. The company recently raised a $355M Series C at a $4.65B valuation and has crossed $300M+ ARR.