About the Role
The role involves advancing the development of world models that enable autonomous vehicles to understand and predict dynamic environments. The engineer will work at the intersection of machine learning, simulation, and robotics to build systems that learn from real-world data and improve driving intelligence.
Responsibilities
- Design and implement machine learning models that simulate real-world environments for autonomous systems
- Collaborate with AI researchers to integrate world models into end-to-end driving pipelines
- Develop scalable simulation frameworks to train and evaluate perception and planning modules
- Improve model accuracy by incorporating sensor data and real-world driving scenarios
- Optimize training workflows for efficiency and computational scalability
- Conduct experiments to validate model predictions against ground truth data
- Refactor and maintain codebases for robustness and reproducibility
- Work closely with engineering teams to deploy models in simulation and real-world testing
- Analyze failure cases to enhance model generalization across diverse conditions
- Stay current with advancements in deep learning, probabilistic modeling, and autonomous systems
Compensation
Competitive salary and equity package
Work Arrangement
Hybrid work model with flexibility for remote and office-based collaboration
Team
Part of a multidisciplinary AI and robotics team focused on building next-generation autonomous vehicle technology
What We Value
- Technical rigor combined with creative problem-solving
- Ownership of projects from concept to deployment
- Collaborative mindset with a focus on team impact
- Curiosity about emerging research and practical applications
Our Approach to Innovation
- We combine cutting-edge research with rapid prototyping
- Emphasis on real-world validation and scalability
- Iterative development informed by data and testing
Visa sponsorship available for qualified international candidates
