Boston Dynamics is building the world’s most advanced robots. The Spot quadruped robot performs inspections on thousands of sites around the world, helping customers to inspect, operate and optimize their industrial facilities.
We are seeking a highly experienced and motivated Principal Machine Learning Engineer to support our Orbit team. Boston Dynamics is uniquely positioned to capture millions of multimodal datapoints from within industrial environments. This data feeds into the Orbit intelligent automation platform, coordinating robot fleets on hundreds of sites today.
In Orbit, we’re building a foundation model with leading zero-shot performance on common industrial inspection tasks. In this role you will have the opportunity to design, build, and continuously improve Orbit’s machine learning systems.
In this role you will:
Be a technical lead on a small team of machine learning engineers.
Research, prototype, and deploy models leveraging multimodal data from robotic sensors to extract useful site information - anomalous machine states, object classification, etc.
Establish effective methods of evaluating inspection model performance.
Curate datasets to be used in model training, fine-tuning and evaluation.
Identify and employ model performance improvement strategies - e.g. fine tuning, model selection, and prompt engineering.
You will be a part of the Asset Owners applications team within the Spot organization. Here you will work alongside full stack engineers and in close coordination with product management and design. You will be supported by ml platform engineers, and collaborate with researchers across Boston Dynamics.
We are looking for:
BS and 10+ years of experience, or MS and 7+ years of industry experience in Computer Science, Machine Learning, Robotics, or a related field.
Expert-level software development skills, particularly in python, with a strong command of software architecture, design patterns, and performance optimization techniques.
Experience training, fine tuning, and applying state of the art generative ai models. Preferably focused on computer vision tasks.
Experience with common ML tools (CUDA, pytorch), architectures and workflows.
Ability to track the current state of the art, and identify opportunities for product applications.
A willingness to dive deep into challenging problems in computer vision, develop creative customer-focused solutions in collaboration with teammates, and clearly communicate findings.