Research Product Manager – AI Systems

Define and build AI evaluation, post-training, and structured data learning systems that improve model performance in production. Partner with researchers and engineers to translate experiments into scalable ML infrastructure.

About the job

Responsibilities

Define and drive systems for model evaluation, benchmarking, and real-world performance
Build product direction for post-training systems and feedback loops that continuously improve models
Define how models learn from large-scale structured and relational datasets
Partner with engineering to build systems that connect data platforms (warehouses, lakehouses) with ML systems
Own how improvements move from research experiments into production systems
Model trade-offs across compute, data efficiency, performance, and cost
Identify where system improvements drive measurable business impact

Requirements

5+ years of experience in product management, technical program management, or similar roles in AI, ML infrastructure, or data systems
Strong understanding of machine learning systems, including training, evaluation, and deployment
Experience working with large-scale data systems or distributed infrastructure
Ability to reason about trade-offs across data, compute, performance, and cost
Track record of driving complex technical systems from concept to production

Nice-to-Haves

Experience with ML platforms, LLM systems, or AI infrastructure
Experience with evaluation systems, observability, or model performance tooling
Familiarity with structured or relational data systems (e.g., warehouses, lakehouses)
Background in engineering, applied research, or ML systems development
Experience operating in research-driven or highly ambiguous environments

Skills

Machine Learning, ML Infrastructure, Model Evaluation, Benchmarking, Post-Training Systems, Structured Data Systems, Data Warehouses, Lakehouses, Distributed Systems, Performance Optimization