Member of Technical Staff - ML Performance
- Location
- New York City, NY
- Job type
- Full-time
- Level
- Mid-level
- Experience
- 5+ years
- Listed
- 31 days ago
Skills & highlights for this role
- PyTorch
- CUDA
- vLLM
- TensorRT
- GPU performance optimization
Also useful
- Linux kernel
- containers
- file systems
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).
About US
AI needs a new infrastructure layer. We're building it at Modal.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Lovable Ramp Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.
Our team includes creators of popular open-source projects (e.g.,Seaborn), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
From Modal's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
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Common questions
Where is the Member of Technical Staff - ML Performance job at Modal located?
This Member of Technical Staff - ML Performance position at Modal is located in New York City, NY. Always check Modal's application page for specific state eligibility or relocation policies.
What qualifications are required for Member of Technical Staff - ML Performance at Modal?
For the Member of Technical Staff - ML Performance role, Modal highlights 5+ years of relevant experience; experience with PyTorch, CUDA, vLLM, TensorRT, GPU performance optimization. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Member of Technical Staff - ML Performance position at Modal?
This listing links directly to Modal's Ashby application page. You can apply directly on Modal's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.