About the Role
As a Senior 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 be responsible for the development and implementation of the latest machine learning techniques that enables better data mining, deep scene understanding, and causal modeling of ego vehicle behavior. The ideal candidate will be able to identify complex edge cases, provide robust algorithmic solutions, and set a high technical excellence bar.
As a Staff 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 the development and implementation of machine learning techniques that enables better data mining, deep scene understanding, and causal modeling of ego vehicle behavior. You aren't just solving known problems; you are identifying the next generation of challenges in AV, designing the architectural foundations to solve them, and raising the bar for technical excellence across the entire engineering organization.
What the Candidate Will Do
Set the technical roadmap and lead the delivery of state-of-the-art Machine Learning systems:
- Algorithm Development: Lead the strategy for development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake.
- Architecture & System Design: Design and oversee the implementation of complex, large-scale ML systems, ensuring seamless integration between upstream sensor data.
- 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.
- Platform Evolution: Define the requirements for high-quality datasets and auto-labeling systems, ensuring our ML infrastructure evolves at the speed of the latest research.
- Cross-Organizational Leadership: Act as a bridge between AV Labs and other Uber engineering units to ensure that autonomous technology is successfully integrated and deployed at scale.
Basic Qualifications
- 8+ 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).
Preferred Qualifications
- PhD degree in Computer Vision, Robotics, or Machine Learning with a focus on Autonomous Driving.
- Extensive experience with C++, CUDA, and high-performance system optimization.
- Deep understanding of the Robot Operating System (ROS) or similar autonomous middleware.
- Recognized expertise in the field (e.g., publications in CVPR, NeurIPS, ICRA or patents related to AV).
- Experience building and scaling \"Foundation Models\" for physical world interaction.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.
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).
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
