Software Engineer, New Grad

BUILD THE DATA INFRASTRUCTURE THAT POWERS PHYSICAL AI.

Physical AI is moving from research labs into production fleets across industries. As robots scale across the real world, from factories to vehicles, to defense - every workflow from product development to deployment becomes a data problem: what happened, when, on which robot, and why?

At Foxglove, we built the unified data platform for physical AI that developer and engineering teams use to answer those questions. We help teams make vast quantities of robotics data actionable, creating the data flywheel they need to develop, test, train, deploy, and operate robots with confidence.

About the Role We're looking for a new grad Machine Learning Engineer to join our team building the ML infrastructure that powers robotics and autonomous systems at scale. You'll work at the intersection of applied ML and production systems — from selecting and deploying models against high-cardinality multimodal robotics data to building the foundational ML tooling that robotics engineers rely on every day. This role is ideal for someone who's excited about physical AI and wants to ship things that work in production, not write papers.

About the team

You will join Foxglove’s Talent function alongside Talent Acquisition, IT, and Workplace. As we scale toward roughly 100 employees across multiple US states and a growing international footprint, this function is building the structure to keep pace. You will partner closely with the VP of Talent, outside employment counsel, our benefits broker, and work cross-functionally with hiring managers and finance.

What you’ll do

- Building and owning inference infrastructure — model serving, scaling, latency/cost optimization (think TorchServe, vLLM, Triton)

- Selecting models for object detection/understanding, embedding computation, text captioning, and more — applied against high-cardinality, multimodal robotics data (video, point clouds, timeseries)

- Standing up semantic...