Job Description
📋 Description Own ML idea to production; collaborate with ML engineers and data scientists. Prioritize platform investments across training, deployment, observability, registry. Drive adoption via usage signals to shape engineering priorities. Measure ML platform success by user outcomes: time saved, models shipped, support load. Improve data trust by defining SLAs, data contracts, ownership. Accelerate AI adoption; identify high-value internal use cases and production. 🎯 Requirements 8+ years PM experience leading complex technical products at Staff or Lead scope. Fluency across data, ML, and AI platforms; able to discuss architecture tradeoffs with engineers. Experience shipping platform products for internal technical users; metrics and adoption. Experience shipping in data-rich marketplaces with data-driven algorithms (search/recommendations/personalization). Cross-functional influence; credibility with senior engineers and data scientists; prioritization. 🎁 Benefits Move fast; own meaningful problems for global customers. Scale with enterprise AI tools to work smarter. Best in class team; growth and craft improvement. Real rewards: pay, equity, and comprehensive benefits. Belonging: equal access to opportunities and growth. Hybrid work: 3 days in office, remote up to 4 weeks/year.
