Senior Engineering Manager, ML Platform at whatnot

This role is designed for a technical leader who enjoys stay "in the weeds" while managing a high-impact team. The ideal candidate has at least 4 years of management experience and a heavy-duty background in building production ML infrastructure for consumer-scale applications. You should be equally comfortable architecting low-latency inference systems and coding—the role expects you to spend about 20% of your time in the codebase. The compensation is highly competitive ($255k–$345k base plus equity), and the company offers a robust suite of perks, including a 4% 401k match and generous "dogfooding" credits to use on their platform. While the team is remote-first, they require you to live within commuting distance of their New York, Seattle, Los Angeles, or San Francisco hubs for occasional in-person collaboration. **You might be a good fit if you...** * Have professional experience with Python and ML frameworks like MLFlow, TorchServe, or Triton. * Are comfortable leading distributed training and managing real-time feature pipelines using Kafka or Flink. * Enjoy a "player-coach" model where you provide architectural guidance and technical feedback while staying hands-on. * Want to build the foundational AI infra for a fast-growing, community-driven marketplace.