Lead the Evaluation Infrastructure team building metrics, evaluation pipelines, and validation platforms for autonomous vehicle safety and iteration. Requires 4+ years experience in distributed systems and ML evaluation, plus strong Python/C++ skills and AI-native engineering practices.
194k – 291k
On-site4+ YOEML Engineering
About the role
Responsibilities
Build and own a unified metrics, evaluation, and validation platform — pipelines, introspection tooling, and analysis products that turn on-road and simulation logs into high-fidelity signals for autonomy iteration and driverless safety validation
Drive the technical bar for metric quality across both heuristic and ML-based approaches
Invest in the scale, reliability, and CI/CD of the evaluation stack to shorten time-to-signal for evaluation and time-to-confidence for validation, and to meet high SLAs for downstream stakeholders
Mentor and grow the Evaluation Infrastructure team, and champion AI-native engineering practices that compound team velocity and code quality
Partner with Product, Autonomy, Systems & Safety, and Simulation teams to define and execute the vision and strategy for evaluation
Requirements
B.Sc or M.Sc. degree plus 4 years of relevant work experience
Strong fluency in distributed systems, large-scale data and ML evaluation pipelines, metrics frameworks (heuristic and/or ML-based), and analytics platforms
Experience setting technical vision, roadmap, and prioritization for a team operating at the intersection of autonomy, safety, and data infrastructure
Clear, concise communicator who partners effectively with PMs, engineers, and cross-functional stakeholders
Ability and willingness to deep-dive into implementation
Sets the technical bar for metric quality, pipeline rigor, and safety-critical engineering practice
Strong proficiency in Python, C++, or similar languages
Daily user of modern AI coding assistants and agentic tools (Claude Code, Cursor, and similar), with strong intuition for where they accelerate engineering work
Nice-to-Haves
Knowledge of data engineering tooling and best practices
Knowledge of batch and streaming data processing, warehousing, and analytics solutions
Experience with data workflow orchestration platforms
Prior experience building evaluation, validation, or analytics platforms, ideally in autonomy, robotics, or safety-critical systems
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194k – 291k
On-site4+ YOEML Engineering
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