Forward Deployed Engineer - ML
Modal Labs · New York · San Francisco
CHECKED 15H AGO
Infrastructureonsite$180k–$250k
At a glance
Highlights
- Partner with leading AI companies to architect and optimize production workloads.
- Build trusted relationships with CTOs and ML leads doing frontier AI work.
- Run demos and proof-of-concepts that make performance advantages tangible.
What they offer
- Equity
Ideal candidate
A curious, customer-obsessed engineer who loves going deep on hard AI problems and thrives translating complex ideas into impact for frontier teams.
Requirements
- 2+ years of professional ML engineering experience
- Hands-on experience with inference optimization, model training, GPU programming, or ML infrastructure
- Familiarity with serving (vLLM, SGLang) or training (slime, verl, TRL) toolchains, with depth in at least one
- Strong communicator able to go deep with engineering teams and articulate tradeoffs to technical leadership
- Genuine interest in working directly with customers to solve hard problems
- Willing to work in-person in New York City, San Francisco, or Stockholm
Lab profile
About Modal Labs
Serverless cloud infrastructure for AI workloads with instant GPU compute.
What they build
- Serverless GPU cloud platform
- Python SDK
- Cloud sandboxes
Known for
- Systems engineering at scale
- ML performance optimization
- Developer-first experience