Principal Software Engineer, ML Infrastructure

In this role, you will

• Vision: Develop and execute a strategic vision for ML Infrastructure that will unlock innovation in autonomous driving and enhance our rider experience. 
• Technical acumen: Lead the design and implementation of cutting-edge infrastructure spanning all stages of an ML lifecycle from data preparation to training to evaluation, deployment, and serving. 
• Partnership: Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.
• Mentorship: Enable the engineers in the team to grow their careers by providing technical guidance and mentorship.

Qualifications

• Experience building and managing large-scale ML infrastructure that powers the development of large-scale ML models
• Excellent leadership skills with a demonstrated ability to lead high-performing engineering teams.
• Strong experience with training frameworks like PyTorch, JAX, etc., leveraging GPUs efficiently for distributed model training.
• Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.
• Proficient in Python and/or C++.

Bonus Qualifications

• Experience enabling the development and deployment of large-scale Foundation models.
• Experience working on large-scale data infrastructure and big data processing frameworks like Apache Spark.
• Experience working in the AV domain supporting Perception, Prediction, Planner et al.