Tech Lead, Perception Autonomy Rivian - 2.7 Palo Alto, CA Job Details Full-time 20 hours ago Qualifications Scalable systems Production systems Model deployment Mapping using 3D modeling Systems engineering Scalability Project execution Benchmarking Model evaluation Sensors MLOps Full Job Description Mapping is a foundational pillar of the Autonomy stack. In this Tech Lead (TL) role, you will own, architect, drive and deliver the strategy to push the frontiers on mapping. The scope includes multi-vehicle mapping (with and without lidar), 3D/4D mapping without lidar, HD maps & localization (including places without GNSS), among other critical applications. You will ship production-grade pipelines that push the boundaries of what's possible in mapping. As such, you will also own and drive the whole end-to-end ML lifecycle & data flywheel for these aforementioned mapping applications: data acquisition, metrics definition, evaluation, model performance optimization, feedback loop. You will also represent these mapping capabilities in our interactions with other teams. You will also work broadly with the rest of the Autonomy org to continuously improve and expand the capabilities of the mapping system as well as defining the requirements. Own, architect, drive and deliver the overarching strategy to push the frontiers on mapping. Scope especially includes multi-vehicle mapping (with and without lidar), 3D/4D mapping without lidar, HD maps & localization, among other critical applications. Ship a production-grade, high-quality, robust, scalable mapping pipeline. 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 mapping system and its capabilities. 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.

Education:

BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a highly related quantitative field.

Experience:

7+ years of professional experience building, scaling and shipping ML solutions, with a strong focus on the following: AV mapping at scale: Proven track record of hands-on experience delivering a mapping system for Autonomous Vehicles at scale.

Architect/Leadership:

Experience with defining, driving and delivering a mapping strategy for AV.

Sensor modularity:

Experience in shipping mapping systems with different sensor modalities in AV, especially both with and without lidar.

Perception stack:

holistic understanding of the entire AV perception stack.

System engineering:

Strong proficiency in Python and/or C++ 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. Preferred Qualifications Strong experience in AV mapping, especially from multiple vehicle passes and across time. Strong experience in Lidar-free mapping for Autonomous Vehicles Experience in building HD maps and SD maps. Experience in Localization given a map, with and without lidar. Experience in defining and driving a 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 auto-labeling (lane, objects, etc) Experience with onboard edge deployment, cloud inference architectures, and balancing compute/efficiency trade-offs. Experience with optimization, hyper-scalability, high-performance inference engines like TensorRT.