Machine Learning Platform Engineer at whatnot

This role is ideal for a mid-to-senior level software engineer (4+ years experience) who specializes in the infrastructure side of AI. You should have a strong background in building production-scale systems, specifically focusing on low-latency model serving, GPU orchestration, and distributed training pipelines. It’s a "builder" role that sits at the intersection of DevOps, Backend Engineering, and Data Science. The compensation is highly competitive, starting at **$245,000+ plus equity**, placing it in the top tier for mid-level roles. While technically "remote co-located," you must live within commuting distance of a major hub (SF, SEA, LA, or NYC) to balance deep work with in-person collaboration. The benefits package is robust, featuring a 4% 401k match, family planning allowances, and a unique monthly budget to "dogfood" the live shopping app. **You might be a good fit if you...** * Have professional experience deploying and scaling LLMs or complex ML architectures in production. * Are proficient in Python and comfortable with cloud-native tools like AWS SageMaker, Kubernetes (EKS), and Kafka. * Enjoy "stretching" into new technical territory to solve high-throughput GPU inference challenges. * Thrive in high-growth startup environments where you own the full lifecycle of a platform.