Principal Software Engineer, ML Infrastructure

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis, and it's a great time to join Zoox and make a significant impact on executing this mission. The ML Infrastructure team at Zoox plays a crucial role in enabling innovations in ML and CV and making autonomous driving as seamless as possible.

The Opportunity

We are seeking a deeply technical, influential, and hands-on Principal Software Engineer to shape and build our next-generation ML Infrastructure and significantly reduce the time to develop and deploy large-scale ML and Foundational models to our robotaxi. You will lead the design and development of our Data, Compute, Model Training, and Serving Infrastructure. You will work across all AI teams within Zoox, including Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.

We build and operate the data infrastructure responsible for ingesting PBs of sensor data and the systems used to assemble training datasets. We operate the compute infrastructure that powers Zoox’s model training, serving, and large-scale validation pipelines across tens of thousands of GPUs. We also operate the base layer of ML tools, deep learning frameworks, and inference systems used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and act as a force multiplier for our teams. You can learn more about our ML Infrastructure here and our stack behind autonomous driving here. 

• 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.

• 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++.

• 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.

Compensation

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $373,000-$448,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.  

Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.