Own the client's recommendation system end-to-end: design, training, deployment, and monitoring
Build and mature ranking and retrieval models that process behavioral signals — clicks, opens, purchases — at consumer scale
Operate ML systems at hundreds of millions of events per day, with direct impact on client revenue
Make independent technical decisions and engage directly with client engineering leadership — no intermediaries

6 to 9 years of experience in software or data engineering roles
4+ years building and operating ML systems in production
2 to 3+ years with recommendation systems as a core area of work — not adjacent exposure
Hands-on experience with ranking and retrieval architectures; able to discuss tradeoffs from real production work
Direct experience operating systems at consumer scale (hundreds of millions of events per day or more)
Strong Python skills and fluency with a modern ML stack: PyTorch or TensorFlow, scikit-learn, feature engineering libraries
SQL fluency for data exploration and validation
Production deployment experience on AWS, GCP, or Azure
Fluent spoken and written English — this role involves direct technical conversation with US client engineering leaders
Demonstrated autonomy in client or stakeholder-facing settings: owning scope, raising blockers, making independent decisions.

Senior ML Engineer

Key skills