engineering
Posted Feb 23Forward Deployed Engineer - ML
at Modal
New York, United StatesOn-site
Requirements
- ABOUT US: AI needs a new infrastructure layer.
- 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.
- 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.
- THE ROLE: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact.
- As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more.
- The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders.
- We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems.
- You will: - Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads on Modal - Contribute to open-source projects — members of the team are active contributors to SGLang — and publish technical content that demonstrates Modal's capabilities across the AI stack - Collaborate with Modal's product and sales teams, contributing to the platform as both an engineer and a product stakeholder - Build trusted relationships with technical leaders (CTOs,
- REQUIREMENTS: - 2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructure - Familiarity with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains.
- You don't need all of these, but you should be able to go deep on at least one.
Benefits
- We've crossed $300M+ ARR and grown fivefold since September.
- - Strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadership - Genuine interest in working directly with customers — you find it energizing to understand someone else's problem and help them solve it - Bonus: side projects, open-source contributions, or published work you're proud of in ML or systems performance - Willing to work in-person in New York City, San Francisco, or Stockholm
Contact
- Our customers include category-defining companies like Lovable https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno.
- We recently raised a $355M Series C https://modal.com/blog/modal-series-c at a $4.65B valuation, led by General Catalyst and Redpoint Ventures.
- Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
Additional details
- 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.
- You're helping teams reach outcomes most engineers can't on their own.