Engineering Lead - Extreme Retrieval

Own the architecture and long-term evolution of a shared engineering platform for retrieval systems. Own the shared repository and codebase for retrieval methods, driving its architecture, extensibility, engineering quality and long-term health. Work with researchers and partner engineering teams to integrate new retrieval methods into a reusable, scalable and well-structured codebase. Improve the developer and researcher experience through clear APIs, examples, tooling and workflows. Drive integration with downstream systems and partner teams so that retrieval methods can be adopted faster and more reliably. Provide cross-team technical leadership, influencing engineering direction and quality standards across collaborating teams. Bachelor's or Masters in Computer Science, Engineering, or related fields. Strong software engineering skills with a proven track record of designing, building, reviewing and maintaining high-quality code in large shared codebases. Significant experience owning or building shared platforms, frameworks, repositories or ML systems used by multiple teams. Strong communication and cross-team collaboration skills, with the ability to drive alignment . High ownership, sound judgment, and the ability to independently drive ambiguous technical problems to completion. Proven ability to work with researchers, engineers, and partner teams to turn research ideas into robust engineering systems. Good understanding of machine learning systems and retrieval methods, such as dense, sparse, or hybrid retrieval, ranking/reranking, and evaluation metrics. Experience building evaluation, benchmarking, or platform infrastructure for machine learning systems. Familiarity with distributed systems, performance optimization, and GPU-backed ML workflows.