Lead and grow an Applied ML team responsible for designing, implementing, and operating scalable evaluation, monitoring and deep-triage systems for AV ML stacks
Own end-to-end ML Monitoring & Triage tool sets: from design, to early prototypes, experiment setup and final productionization.
Develop AI/ML-powered triage agents that dives deep into performance issues and generates solution level triage and root cause
Partner cross-functionally with AI/ML, simulation, systems, safety, and product teams to identify the most important signals and scenarios to evaluate, and to prioritize improvement opportunities for the ML stack.
Create clear, compelling narratives and reports that synthesize complex data into actionable insights for senior leaders and partner teams, enabling informed, timely launch and continuous deployment decisions.
Foster a high-performance, inclusive team culture focused on accountability, rigorous thinking, healthy debate, and continuous learning.
Establish and refine team processes (prioritization, planning, execution, incident reviews) to ensure reliable, scalable, and repeatable delivery of evaluation results.

Bachelor’s degree in Computer Science, Electrical/Computer Engineering, Robotics, Applied Mathematics, or a related technical field, or equivalent practical experience.
2+ years of people management experience leading engineering, validation, or applied ML teams.
5+ years of experience in one or more of: applied ML, systems engineering, validation/verification, or evaluation for complex software or autonomy systems.
Demonstrated end-to-end ownership from problem definition through methodology design, implementation, analysis, and driving concrete product outcomes.
Proven analytical and systems engineering skills in highly complex, ambiguous technical domains (e.g., end-to-end ML stacks, robotics, or distributed systems).
Experience designing or operating evaluation or validation pipelines that leverage both simulation and real-world data.
Strong communication skills, with a track record of aligning diverse stakeholders and presenting complex technical concepts to mixed technical and non-technical audiences.

Applied AI/ML Evaluation & Monitoring Manager – Autonomous Vehicle

Key skills