Forward Deployed Engineer - ML
Modal Labs, Inc. operates Modal, a serverless cloud and AI infrastructure platform for developers running inference, training, batch processing, and isolated sandboxes.
Funding history
About Modal
Modal provides code-first, elastic CPU/GPU compute infrastructure for AI workloads, including model inference, fine-tuning and training, large-scale batch jobs, and secure ephemeral execution environments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will work hands-on with leading AI companies and foundation model labs to architect and optimize demanding production workloads such as LLM serving, model training, audio pipelines and scientific computing. You will contribute to open-source projects, publish technical content, collaborate with product and sales teams, build relationships with technical leaders, and run demos, experiments and proofs of concept.
Requirements
- 2+ years of professional ML engineering experience, ideally in inference optimization, model training, GPU programming or ML infrastructure
- Familiarity with serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains, with depth in at least one
- Strong communication skills for discussing technical architecture and tradeoffs
- Genuine interest in working directly with customers
- Willingness to work in person in London
Responsibilities
- Work hands-on with customers to architect and optimize production AI workloads on Modal
- Contribute to open-source projects and publish technical content
- Collaborate with product and sales teams
- Build trusted relationships with technical leaders such as CTOs, VPs of Engineering and ML leads
- Conduct technical demos, experiments and proofs of concept