Join Microsoft Research India to redefine information retrieval at scale. We are looking for a highly motivated individual contributor to lead ML codebase development and build the software engineering platform for a significant project focused on large-scale machine learning for retrieval. This role is at the nexus of research and engineering, aiming to establish the foundational engineering practices for translating retrieval research into adaptable and widely adopted systems across Microsoft products.

This position offers the unique opportunity to work with a world-class team of researchers and engineers, reporting directly to a Distinguished Scientist and Vice President. You will significantly influence the future of retrieval technology within Microsoft, shaping engineering standards, core interfaces, and evaluation frameworks. Your contributions will be instrumental in how new retrieval methods are developed, validated, and integrated, with potential to present findings to senior leadership and influence strategic direction.

Take ownership of the architecture and long-term evolution of a shared engineering platform specifically designed for retrieval systems. Lead the development and maintenance of the shared repository and codebase for retrieval methods, ensuring its architecture, extensibility, engineering quality, and long-term health.

Collaborate closely with researchers and partner engineering teams to seamlessly integrate novel retrieval methods into a scalable and well-structured codebase. Enhance the developer and researcher experience by providing clear APIs, comprehensive examples, efficient tooling, and streamlined workflows. Drive the integration of retrieval methods with downstream systems and partner teams to accelerate and improve the reliability of adoption.

A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is required. Essential are strong software engineering capabilities, demonstrated through a history of designing, building, reviewing, and maintaining high-quality code within large, shared codebases. Significant experience in owning or developing shared platforms, frameworks, repositories, or ML systems utilized by multiple teams is crucial.

Exceptional communication and cross-team collaboration skills are necessary to drive alignment and consensus. High levels of ownership, sound judgment, and the ability to independently resolve complex technical challenges are expected. A proven ability to translate research concepts into robust engineering systems through collaboration with researchers, engineers, and partner teams is highly valued. Familiarity with machine learning systems and various retrieval methods, alongside experience building evaluation or benchmarking infrastructure for ML systems, would be advantageous.