Senior Principal Machine Learning Systems Engineer, Search Platform

About the role

The Search Platform team powers Rovo Search and knowledge discovery for humans and agents across all enterprise data, aiming to make customer knowledge searchable, secure and reliable. As technical lead for Search Serving, you set its long-term technical direction and own end-to-end search quality, tail latency, reliability, scalability, operability and cost. You work with Relevance, Search Data and Product to bring new ML capabilities to the search experience.

Key responsibilities

• Design and build high-quality agentic search systems covering tail latency, throughput, concurrency, caching, sharding, fault isolation, capacity and graceful degradation.
• Define the long-term architecture and roadmap for online retrieval, index serving, query processing and ML inference, turning research advances into production systems.
• Establish ML production practices: offline and online evaluation, experimentation, observability, safe rollout and rollback, model-quality regression and incident response.
• Improve production inference for embedding, retrieval and ranking models using batching, quantization, distillation, compilation and hardware-aware optimization.
• Lead step-change initiatives across teams, simplify fragmented systems, mentor senior engineers and align technical and product leaders on long-term direction.

Required profile

• 10+ years of relevant experience, including designing and operating large-scale, low-latency search, recommendation, advertising or retrieval systems.
• Track record of setting cross-organization technical direction and resolving consequential architecture choices across multiple teams and senior leaders.
• Strong product and technical judgment: framing important problems, testing hypotheses, comparing alternatives and stopping investments that do not justify their complexity.

Required skills

• Deep ML systems experience: production inference, model optimization, retrieval and ranking pipelines, evaluation, experimentation and operations.
• Distributed systems expertise: performance, concurrency, availability, multi-tenancy, capacity planning, observability and cost efficiency.
• Information retrieval and applied ML foundations, with experience in lexical, semantic, vector or hybrid retrieval.

What we offer

• Base pay for new hires in the US: Zone A $272,700-$356,025, Zone B $245,430-$320,423, Zone C $226,341-$295,501; eligibility for benefits, bonuses, commissions and equity.
• Flexible working: office, home or a mix, and the option to work remotely.
• Health and wellbeing resources and paid volunteer days.