Uber is launching - - AV Labs - - to accelerate the autonomous technology ecosystem. We’re building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team is focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race—and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match. As a Senior ML Engineer, you will be at the forefront of - - Physical AI - - , developing core components of our - - Autonomous Driving - - stack. You will be responsible for the development and implementation of the latest machine learning techniques across - - the autonomy - - systems. The ideal candidate will be able to identify complex edge cases, provide robust algorithmic solutions, and set a high technical excellence bar. You will collaborate with engineers across big data, compute, and cloud engineering to build platforms that harness scale and real-world complexity to reimagine how the world moves. ## - - What the Candidate Will Do - - - - - Autonomous Driving Algorithm Development: - - Lead the development of algorithms to tackle complex urban environments, focusing on robustness and safety. - - - End-to-End AI Implementation: - - Implement end-to-end AI-driven state-of-the-art methods for autonomy pipelines, leveraging massive-scale real-world data. - - - Systems Architecture Design: - - Architect scalable ML systems, including management of upstream sensor dependencies. - - - Technical Leadership: - - Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability. - - - Dataset Optimization: - - Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling. - - - Cross-Functional Collaboration: - - Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production. ## - - Basic Qualifications - - - 4 years of working experience in the ML/ Robotics industry. - Bachelor’s degree in Computer Science, Computer Engineering, or related fields. - Proficient in Python and Linux environments. - Familiar with modern AI/ ML frameworks (e.g., Py. Torch). ## - - Preferred Qualifications - - - Experience in the Autonomous Driving domain. - Proven track record of deploying ML models in safety-critical physical systems. - Master’s or PhD degree in Computer Vision, Robotics, or Machine Learning. - Familiarity with C and high-performance computing. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.