Software Engineer, Zoox

• 6+ years of experience
• Proficient in Python or C++
• Familiarity with any of the training frameworks and libraries like PyTorch, Lightning, Hugging Face, Ray, JAX, etc
• Familiarity with any of the GPU-accelerated inference on Nvidia hardware like CUDA, TensorRT, and/or XLA

Desirable

• Would you like to enable ML use cases like autonomous driving, scene understanding, and automated mapping at Zoox?
• This role works across all ML teams within Zoox - Perception, Behavior ML, Simulation, Data Science, Collision Avoidance, as well as with our Advanced Hardware Engineering group specifying our next generation of autonomous hardware
• You will significantly push the boundaries of how ML is practiced within Zoox
• We build and operate the base layer of ML tools, deep learning frameworks, inference libraries, and ML infrastructure used by our applied research teams for in- and off-vehicle ML use cases
• We coordinate across all of Zoox to make sure that the needs of both the vehicle and ML teams are met
• You will play a crucial role in reducing the time it takes from ideation to productionization of cutting-edge AI innovation
• This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains
• Design, develop, and deploy custom and off-the-shelf ML libraries and toolings to improve ML development, training, deployment, and on-vehicle model inference latency
• Build tooling and establish development best practices to manage and upgrade foundational libraries, i.e., Nvidia driver, PyTorch, TensorRT, etc., improve ML developer experience, and expedite debugging efforts
• Collaborate closely with cross-functional teams, including applied ML research, high-performance compute, advanced hardware engineering, and data science, to define requirements and align on architectural decisions