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 serving toolchains (e.g., vLLM, SGLang) and training toolchains (e.g., slime, verl, TRL), with deep expertise in at least one
• Strong communication skills for discussing technical architecture with engineering teams and articulating tradeoffs to technical leadership
• Genuine interest in working directly with customers to understand and solve their problems
• Willingness to work in person in New York City, San Francisco, or Stockholm

Nice to Haves

• Side projects, open-source contributions, or published work in ML or systems performance

What You'll Be Doing

• Work hands-on with companies like Suno, Cognition, and Meta to architect and optimize production AI workloads on Modal
• Contribute to open-source projects and publish technical content showcasing Modal’s AI stack capabilities
• Collaborate with Modal’s product and sales teams, acting as both engineer and product stakeholder
• Build trusted relationships with technical leaders at frontier AI companies
• Conduct technical demos, experiments, and proofs of concept to demonstrate Modal’s performance advantages