Member of Technical Staff - ML Performance

Modal; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

A leading AI infrastructure company based in New York is seeking experienced engineers to enhance the performance of ML systems and contribute to open-source projects. Ideal candidates will have over 5 years of experience in writing high-quality code and familiarity with Nvidia GPU architecture and ML frameworks. This role offers opportunities for significant growth within a fast-growing team and requires in-person collaboration in NYC, San Francisco, or Stockholm.

Qualifications

• 5+ years of experience writing high-quality, high-performance code.
• Experience working with high-level ML frameworks.
• Familiarity with Nvidia GPU architecture and CUDA.

Responsibilities

• Contribute to open-source projects related to ML systems.
• Optimize container runtime for better model performance.
• Debug and optimize GPU performance.

Skills

High-quality code writing

Performance optimization

Experience with torch

Familiarity with Nvidia GPU architecture

Experience with CUDA

Tools

TensorRT

vLLM

Job description

About Us:

Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub‑second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low‑latency inference. Companies like Suno, Lovable, and Substack rely on Modal to move from prototype to production without the burden of managing infrastructure.

We're a fast‑growing team based out of NYC, SF, and Stockholm. We've hit high 8‑figure ARR and recently raised a Series B at a $1.1B valuation. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.

Working at Modal means joining one of the fastest‑growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. Our team includes creators of popular open‑source projects (e.g. Seaborn, Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

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).
• Ability to work in‑person, in our NYC, San Francisco or Stockholm office.