Job Description
The Machine Learning Engineer - Models and Validation at Aurora is responsible for developing and evaluating machine learning models for self-driving vehicle systems, including motion planning and simulation data augmentation, while collaborating with various engineering teams to ensure robust deployment and performance.
Key Responsibilities
- Build and evaluate learned models for the Motion Planner in large-scale simulations
- Develop generative models to augment simulation data and create realistic scenarios
- Support ML model development workflow, including dataset management, label quality, and feature processing
- Collaborate with Behavior Planning and Safety Engineering teams to understand requirements and inform technical approaches
- Work with Simulation teams to deploy models and add necessary core functionalities
- Create tools for visualizing, introspecting, and extracting insights from models
- Participate in code reviews and contribute ideas within a collaborative environment
Requirements
- Motivated and able to work independently in a fast-paced environment, navigating problem ambiguity.
- Strong knowledge of machine learning fundamentals.
- Experience in building machine learning models, including data preparation, training, model design, and evaluation.
- Robotics-related domain knowledge.
- Proficiency with PyTorch, Python, numpy, and common data science libraries.
- At least 2 years of industry experience in a related field.
Benefits & Perks
Base salary range: $139,000 - $223,000 per year
Annual bonus
Equity compensation
Hybrid work environment with in-office presence at least 3 days per week
Ready to Apply?
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