Senior Engineering Manager, ML Platform at whatnot

This role is designed for a highly technical leader who thrives at the intersection of infrastructure and AI. You should have at least 4 years of engineering management experience and 5+ years of hands-on experience building production systems for high-traffic consumer platforms. The ideal candidate is a "builder" who stays in the weeds, coding at least one day a week while managing the systems that power low-latency model serving, streaming feature ingestion, and distributed GPU training. The compensation is a major highlight, offering a base salary up to **$345k plus equity**, a 401k match, and unique lifestyle perks like a "dogfooding" budget to shop on the app. While the role is listed as on-site/co-located in major hubs (SF, NY, LA, or Seattle), it offers a balance of office connection and home flexibility. You'll have significant influence over the architecture of a fast-growing marketplace during a critical AI expansion. **You might be a good fit if you...** * Have deep experience with Python and ML frameworks like TorchServe, Triton, or MLFlow. * Are comfortable designing real-time feature pipelines using Kafka, Flink, or DynamoDB. * Enjoy a "player-coach" model where you provide high-level strategy but still contribute to the codebase. * Want to solve complex scaling challenges involving high-throughput GPU inference and distributed training.