About the Role
As a Principal ML Engineer, you will be at the forefront of Physical AI, building advanced autonomy algorithms and models to add rich semantics to our massive driving data. You will set the technical direction for developing state-of-the-art machine learning that enables better data mining, deep scene understanding, and causal modeling of ego vehicle behavior. You aren't just solving known problems; you are architecting the intelligence behind our L4 data and evaluation engine. 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 You'll Do
- Strategic Semantic Modeling: Lead the strategy for developing autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake
- Scene and Behavior Causality Understanding: Provide the overarching technical vision for multi-modal scene understanding and modeling the causality behind ego vehicle behaviors from logged data. You will lead the design of state-of-the-art models to achieve highly accurate, real-world interpretation of the data. By understanding the 'why' behind driving decisions in complex scenarios, you will spearhead the creation of a comprehensive, highly structured taxonomy for our autonomous database, creating the ultimate data mining engine that empowers partners to query and extract precise edge cases
- Technical Mentorship & Influence: Mentor senior and lead engineers, fostering a culture of rigorous experimentation and engineering excellence. You will influence the technical direction of multiple teams
- Cross-Organizational Leadership: Act as a bridge between AV Labs and other Uber engineering units to ensure our semantic models and data evaluation platforms are successfully integrated and deployed at scale
What you'll Need
- 10+ years of working experience in the ML, Robotics, or Autonomous Systems industry
- Proven experience leading large-scale technical projects from conception to production
- Bachelor's degree in Computer Science, Computer Engineering, or related fields
- Expert-level proficiency in Python and Linux environments
- Deep expertise in modern AI/ML frameworks (e.g., PyTorch, TensorFlow)
Bonus Points If
- PhD degree in Robotics or Machine Learning with a focus on Autonomous Driving, Computer Vision, or foundation models
- Extensive experience with C++, CUDA, and high-performance system optimization for massive offline datasets
- Deep understanding of autonomous system architectures, sensor data pipelines, and offline evaluation simulation
- Experience building and scaling \"Foundation Models\" for physical world interaction, scene representation, or causal behavior modeling
- Recognized expertise in the field (e.g., relevant patents, open-source contributions, or publications)
For San Francisco, CA-based roles: The base salary range for this role is USD$302,000 per year - USD$336,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$302,000 per year - USD$336,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits).
