We're looking for a software engineer to help build and refine the core systems behind end-to-end autonomous driving technology. In this role, you'll design and implement machine learning tools and infrastructure that power large-scale research, working closely with both AI researchers and engineering teams to transition experimental models into reliable, production-grade software.
What You'll Do
- Develop scalable tools and systems that support end-to-end training workflows, enabling faster iteration and deployment of AI models
- Collaborate with research teams to identify performance bottlenecks in data processing, compute utilization, and evaluation pipelines
- Design modular software solutions that streamline development across the ML stack—from on-vehicle components to cloud infrastructure
- Work with massive real-world driving datasets, improving curation, access, and integration into training and testing environments
What We're Looking For
- Proven ability to write clean, maintainable code across multiple layers of the ML pipeline, with strong fundamentals in abstraction and system design
- Strong problem-solving skills and the ability to quickly analyze and resolve complex technical challenges
- Familiarity with large-scale compute environments, distributed systems, or cloud-based ML platforms
- Hands-on experience with Python, PyTorch, CUDA, and modern build or orchestration tools such as Bazel or Kubernetes
Why This Matters
The work you do will directly influence the pace and reliability of autonomy development, helping scale training efforts in tandem with growing data volumes, GPU capacity, and evaluation needs. You'll have ownership over critical infrastructure and the chance to shape how AI models are developed, tested, and deployed.
Compensation & Benefits
This role offers a competitive base salary ranging from $153,000 to $222,000 annually, equity in the form of stock options or restricted stock units, and additional support through learning and wellness stipends. Comprehensive health, dental, and vision coverage, 401k with employer matching, and paid time off are also included.
Work Environment
This is primarily an onsite role with offices in multiple global locations. Teams typically work from the office five days a week, though limited flexibility is available for remote work when needed for personal commitments. Regular collaboration with cross-functional teams is a key part of the workflow.
Our Culture
Engineers here take full ownership of technical and product decisions, with direct input into system architecture and development priorities. We value close collaboration with end users—both internal and external—to gather insights and refine our tools. The environment is thoughtful and adaptive, encouraging innovation while maintaining engineering rigor.
Equal Opportunity
We are committed to equal employment opportunity and comply with all applicable federal regulations prohibiting discrimination. Decisions are based on merit, qualifications, and experience without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. We also uphold employee rights under federal labor laws.
