Senior Engineering Manager, AV Labs

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 Sr. Manager of Engineering, you will lead a highly specialized team of machine learning engineers and applied researchers focused on AI models and behavioral causality. You will guide the execution and development of state‑of‑the‑art foundation models that parse complex urban edge cases, driving the technical roadmap to add rich semantics to our massive driving data. By leading the charge on understanding the "why" behind driving decisions, your team will power the L4 data and evaluation engine that serves as the ultimate data‑mining platform for our autonomous partners. What You Will Do Team Leadership & Growth: Build, manage, and mentor a high‑performing engineering team of ML experts, AI modelers, and data scientists. Foster a culture of rigorous scientific experimentation, high‑velocity execution, and engineering excellence. AI Model Execution: Drive the day‑to‑day development of advanced autonomy algorithms and foundation models. Ensure your team successfully extracts high‑fidelity semantic meaning from multimodal sensor data to enrich our L4 data lake. Technical Strategy & Engineering Rigor: Collaborate with technical leadership to steer foundational architectural choices. Maintain uncompromising quality for deployed systems, ensuring performance is tuned for low‑latency execution of large scale data. Cross‑Functional Collaboration: Partner closely with Directors, Principal Engineers, Product Managers, and infrastructure teams to align your team’s ML modeling efforts with broader business goals and ensure seamless deployment at scale. Basic Qualifications 8+ years of software engineering experience in applied ML, AI modeling, or Autonomous Systems. 3+ years of experience managing engineering teams, with a track record of leading high‑performing ML or AI organizations. Proven experience delivering complex, large‑scale AI models or ML pipelines from conception to production. Bachelor’s degree in Computer Science, Computer Engineering, or related fields. Deep expertise in modern AI/ML frameworks (e.g., PyTorch, TensorFlow) and Python/Linux environments. Preferred Qualifications Advanced degree (MS or PhD) in Robotics, Machine Learning, Computer Vision, or a related field. Deep technical understanding of AI foundation models, multimodal perception, and causal behavior modeling. Prior experience in the Autonomous Vehicle (AV) industry, specifically focused on offline evaluation, 3P data understanding, or autonomous data mining (as opposed to embedded on‑car execution). Strong background in guiding teams to build models that process, structure, and query massive datasets to enable advanced scene representation. Excellent communication skills with the ability to translate complex technical concepts into strategic roadmaps for cross‑functional partners. For all US locations, the base salary range is USD$267,000 per year - USD$297,000 per year. All full‑time employees are eligible to participate in a 401(k) plan and may be offered an equity award and other compensation. Equal Opportunity Employer Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form. #J-18808-Ljbffr Uber