AI Systems Engineer, Tooling & Infrastructure, Optimus

As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture by building and automating scalable data and inference pipelines, ensuring data quality by building visualizing tools. We are building a Machine Learning Platform that automates the collection, processing, and evaluation of data, reducing manual overhead and accelerating the entire ML lifecycle. We are seeking an experienced engineer to build this automation platform that translates research breakthroughs into robotic intelligence at scale. The systems you create will drive continuous data integration, automated evaluation, and rapid deployment—impacting how thousands of Humanoid Robots perceive and act in the real world every day.

Responsibilities

Automate data, inference, and auto-labeling pipelines Build the tooling and infrastructure for reporting and visualizing model metrics and performance Manage, analyze, and validate our training and test datasets Coordinate with the team managing the hardware cluster to maintain high availability / jobs throughput for Machine Learning Drive implementation of best practices and monitoring systems to proactively detect and address issues in our production environment Build and improve our Python training infrastructure for stable and faster training and validate our PyTorch models

Requirements

Strong programming experience in Python and vectorization APIs such as numpy Experience with distributed compute systems (k8s, Slurm, LSF, etc.) or experience with large datasets / data workflows Experience working in a team environment It would be a plus if you have experience in training deep learning models and designing and deploying automation systems for machine learning workflows