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.
• 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 Stockholm