Forward Deployed Engineer - ML (London)
Modal Labs · London
Infrastructureonsitemid
At a glance
Highlights
- Partner with leading AI companies and labs on demanding production workloads.
- Architect and optimize LLM serving, training, and audio pipelines at scale.
- Publish technical content demonstrating Modal's capabilities across AI stack.
Ideal candidate
A curious, customer-obsessed engineer who loves deep technical problem-solving and direct customer impact. You thrive partnering with frontier AI teams and clearly communicating tradeoffs to both engineers and leaders.
Requirements
- 2+ years of professional ML engineering experience, ideally in inference optimization, model training, GPU programming, or ML infrastructure
- Familiar with serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains, with depth in at least one
- Strong communicator able to discuss technical architecture with engineers and tradeoffs with technical leadership
- Genuine interest in working directly with customers to understand and solve their problems
- Willing to work in person in London
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
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