Member of Technical Staff - ML Performance

Modal, Inc

• $160K — $190K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in high-performance coding
  • Proficient with torch and high-level ML frameworks
  • Experience with inference engines like vLLM or TensorRT
  • Familiar with Nvidia GPU architecture and CUDA
  • Background in ML performance engineering, particularly GPU optimization
  • Nice-to-have: knowledge of low-level OS foundations like Linux kernel and containers

Responsibilities

  • Develop and optimize ML systems for performance at scale
  • Contribute to open-source projects related to Modal's container runtime
  • Enhance throughput and reduce latency for language and diffusion models
  • Debug and resolve GPU performance issues
  • Rewrite algorithms to improve compute efficiency

Benefits

  • Opportunity to work on cutting-edge ML technologies
  • Engagement in open-source contributions
  • Collaborative work environment with a focus on innovation
  • Potential for professional growth in a high-impact role
Full Job Description
The Role:

We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal's container runtime to push language and diffusion models towards higher throughput and lower latency, we'd love to hear from you!

Requirements:
  • 5+ years of experience writing high-quality, high-performance code.
  • Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT).
  • Familiarity with Nvidia GPU architecture and CUDA.
  • Experience with ML performance engineering (tell us a story about boosting GPU performance - debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc).
  • Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

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