Senior Principal Machine Learning Systems Engineer, Search Platform

Responsibilities

• Design and build high quality agentic search systems, addressing tail latency, throughput, concurrency, caching, sharding, fault isolation, capacity, and graceful degradation.
• Set the long-term architecture and technical roadmap for online retrieval, index serving, query processing, and ML inference. Turn advances in information retrieval and machine learning into production systems through rigorous evaluation, experimentation, and incremental adoption.
• Establish strong ML production practices spanning offline and online evaluation, experimentation, observability, safe rollout and rollback, model-quality regressions, and incident response.
• Advance production inference for embedding, retrieval, and ranking models through techniques such as batching, quantization, distillation, compilation, and hardware-aware optimization.
• Lead step-change initiatives across multiple teams, simplify fragmented systems, mentor senior engineers, and align technical and product leaders around long-term direction. Uplevel team and platform maturity to best-in-class agentic development practices to accelerate innovation.

Languages