Senior Tech Lead Manager, Perception
About The Position
Auto-labelling is a foundational pillar of the Autonomy stack. In this Senior Tech Lead Manager (TLM) role, you will own, architect, drive and deliver the overarching strategy for Lidar-free auto-labeling at large scale. This scope includes mapping, lanes auto-labelling, object auto-labelling, scaling as well as other critical applications. You will ship production-grade models that push the boundaries of what’s possible. As such, you will also own the whole end-to-end ML lifecycle of this scope: data acquisition, metrics definition, evaluation, model performance optimization, feedback loop. You will also work broadly with the rest of the Autonomy org to continuously improve and expand the capabilities of the system as well as defining the requirements. As TLM, this role will include managing individual contributors (IC) supporting those activities.
Requirements
- BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a highly related quantitative field.
- 7+ years of professional experience scaling ML solutions, with a strong focus on the following:
- AV auto-labeling system at scale: Proven track record of hands-on experience delivering an auto-labeling system for Autonomous Vehicles at scale. Auto labeling for mapping, lanes auto-labelling and/or object auto-labelling.
- Auto-labeling architect: Experience with owning, driving and delivering an auto-labeling strategy for AV.
- Perception stack: holistic understanding of the entire AV perception stack.
- System engineering: Strong proficiency in Python alongside a solid understanding of modern Perception pipelines, benchmarking tools, and infrastructure.
- Execution: Demonstrated ability to drive progress across a complex system spanning multiple domains and components, across a distributed, cross-functional stack in a fast-paced environment.
- Team management: experience managing software, robotics and/or machine learning teams.
Nice To Haves
- Strong experience in Lidar-free lane auto-labeling
- Strong experience in mapping, especially from multiple vehicle passes
- Experience in driving training data strategy, including defining data annotation guidelines, partnering effectively with in-house and external 3P annotation vendors.
- Experience with multiple modalities (e.g., cameras, LiDAR, Radar).
- Experience with onboard edge deployment, cloud inference architectures, and balancing compute/efficiency trade-offs.
- Experience with quantization techniques (PTQ, QAT) and high-performance inference engines like TensorRT.
Responsibilities
- Own, architect, drive and deliver the overarching strategy for Lidar-free auto-labeling at large scale. This scope includes AV mapping, lanes auto-labelling, object auto-labelling and scaling.
- Ship production-grade, scalable auto-labeling models.
- Have a holistic understanding of the entire AV perception stack and work with the teams to define how we measure and monitor performance of the auto-labeling system.
- Work with the team to drive progress in improving the performance. Establish rigorous evaluation and monitoring benchmarks. Identify and root-cause top-tier system anomalies, prioritizing high-impact optimizations to continuously push the needle on performance.
- Partner closely with the Autonomy group to ensure we meet the feature requirements
- Define system requirements and guide cross-functional efforts through technical trade-off decisions.
- Manage individual contributors (IC) responsible for supporting the aforementioned responsibilities
Benefits
- paid vacation
- paid sick leave
- life insurance
- medical insurance
- dental insurance
- vision insurance
- short-term disability insurance
- long-term disability insurance
- 401(k) Plan
- Employee Stock Purchase Program
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What This Job Offers
Job Type
Full-time
Career Level
Senior
