Hybrid opportunity at
ZooxSoftware Engineer - Learned Trajectory Machine Learning Engineer
Zoox is building a purpose-built, fully autonomous vehicle fleet designed for urban mobility services, combining robotics, machine learning, and vehicle design. The Prediction and Behavior Machine…
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About This Role
Zoox is building a purpose-built, fully autonomous vehicle fleet designed for urban mobility services, combining robotics, machine learning, and vehicle design. The Prediction and Behavior Machine Learning team creates algorithms that interpret data and predict actions, deploying them both directly on vehicles and within off-vehicle simulation and validation systems. This position operates on a hybrid schedule. As a Learned Trajectory Machine Learning Engineer, you will build deep learning architectures using…
Job Description
Zoox is building a purpose-built, fully autonomous vehicle fleet designed for urban mobility services, combining robotics, machine learning, and vehicle design. The Prediction and Behavior Machine Learning team creates algorithms that interpret data and predict actions, deploying them both directly on vehicles and within off-vehicle simulation and validation systems. This position operates on a hybrid schedule.
As a Learned Trajectory Machine Learning Engineer, you will build deep learning architectures using imitation learning and reinforcement learning to formulate driving paths for autonomous cars. Your work will involve assessing the safety, comfort, and progress of these driving routes. You will utilize large-scale machine learning infrastructure, create error-analysis tools, and build measurement metrics. Because trajectory forecasting directly impacts motion planning, you will work hand-in-hand with the Planner, Perception, Simulation, and Systems Engineering groups.
This opportunity fits professionals skilled in machine learning who want to advance autonomous driving technology in dense city settings. Ideal candidates possess strong algorithmic backgrounds and a foundation in programming.
Responsibilities
- Design new deep learning models utilizing reinforcement learning and imitation learning to create driving routes for self-driving cars
- Evaluate the quality of driving plans according to safety, progress, and comfort metrics
- Utilize large-scale machine learning infrastructure to investigate new approaches
- Build tools and metrics to evaluate system improvements and analyze errors
- Partner with Perception, Simulation, and Planning engineering teams to address autonomous driving challenges in complex cities
Requirements
- Hold a BS, MS, or PhD degree in computer science or a related discipline
- Bring practical experience training and deploying transformer-based model architectures and reinforcement learning
- Demonstrate experience with production machine learning pipelines, including training frameworks, metrics pipelines, and dataset creation
- Show fluency in either C++, or fluency in Python combined with a basic understanding of C++
- Possess extensive programming and algorithm design experience
- Demonstrate strong mathematics skills
Qualifications
- Have conference or journal publications in robotics or machine learning venues
- Bring previous experience in robotics, autonomous vehicles, or prediction
Core Skills
Frequently Asked Questions
What is the remote work policy for this role?
The position is offered on a hybrid basis.
What education level is required to apply?
Applicants must hold a Bachelor of Science, Master of Science, or PhD degree in computer science or a related field.
What programming languages are needed?
Candidates must be fluent in C++, or fluent in Python with a basic understanding of C++.
What is the salary range for this position?
The job posting does not specify a salary range.
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