Staff Machine Learning Engineer - Vision AI

Required

• Deep engineering experience. 10+ years building software, including designing and shipping distributed systems and data pipelines in production at scale.
• Backend and cloud expertise. Strong experience with cloud infrastructure (AWS preferred), event-driven systems (e.g. Pulsar or Kafka), storage, and APIs, in Kotlin, Java, or similar languages, plus comfort with Python.
• Experience with ML systems and video. You don't need to be a model researcher, but you understand how models are trained, tuned, and served, and you've built and operated ML systems in production, including inference pipelines, evaluation, and model monitoring. You're also comfortable working with video (streams, codecs, tools like ffmpeg).
• Pragmatic architecture. A track record of designing systems that fit the current stage, avoiding over-engineering while leaving room to grow.
• Zero-to-one experience. Experience taking ambiguous ideas from prototype to production with real customers.
• Hands-on keyboard. You still write significant production code and enjoy doing it.
• AI-forward ways of working. Daily use of AI coding assistants and agent harnesses (e.g. Claude Code, Cursor), and experience building with LLM or vision-language model APIs.
• Collaboration and communication. Ability to align engineers, product partners, and other orgs around technical decisions and explain tradeoffs clearly.
• This role may not be a fit for you if...
• You want a primarily cross-org or architecture-only role. This is a hands-on keyboard role. You'll spend most of your time building, with cross-org collaboration when the work requires it.
• You're more attached to the solution than the problem. We want someone obsessed with solving real problems for restaurant operators, who picks the simplest approach that solves them.
• You tend to build for scale before it's needed. We need someone who builds the right solution for where we are today and what customers are telling us, while keeping long-term direction in mind and knowing when to invest in it.