Applied ML Triage, Evaluation & Monitoring Tech Lead

Job Description

As an Applied ML Triage, Evaluation & Monitoring Tech Lead on the Software Validation team within the AV organization, you will lead developments around building and operating ML-driven evaluation tools, systems and executions that enable safe, comfortable, and intuitive autonomous driving at scale. Your work will transform the way we monitor the changes in the end-to-end ML stack for Autonomous Vehicles, designing and deploying centric tool sets which makes performance monitoring seamless and automated, and enables scalable and deep causal analysis to get to the roots of problem space for effective engineering iterations.

You will partner closely with AI/ML engineers, simulation engineers, systems engineers, and product managers to design, implement, and maintain robust evaluation and validation processes that combine simulation and on-road data. Your work will drive systematic, data-driven improvements to AV software performance and help connect day-to-day monitoring and triage work to the engineering roadmap for continuous improvement and burn down of problem space.

This role combines hands-on technical leadership in applied ML evaluation and team building. You will lead cross-functional initiatives, shape the roadmap for evaluation capabilities, and foster a culture of ownership, curiosity, and high-quality execution.

What You'll Do

Lead Applied ML projects 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 produtionization.

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.

Your Skills & Abilities

Bachelor’s degree in Computer Science, Electrical/Computer Engineering, Robotics, Applied Mathematics, or a related technical field, or equivalent practical experience.

2+ years of 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.

What Will Give You A Competitive Edge

Graduate degree (MS/PhD) in a relevant technical field (e.g., ML, robotics, control, statistics, systems engineering).

Experience building or leading teams in autonomous vehicles, robotics, or safety-critical systems.

Hands-on experience with ML-based autonomy systems, including familiarity with model evaluation, failure analysis, and performance debugging in real-world conditions.

Track record of growing and mentoring engineers, including performance management, career development, and building inclusive, diverse teams.

Comfortable working in fast-paced, highly ambiguous environments, with the ability to balance strategic thinking and hands-on execution.

Compensation

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area. The salary range for this role is $218,800 and $335,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the pos