Build the data infrastructure for robots operating in the real world.

Robotics is moving from research labs into production across factories, warehouses, vehicles, and field deployments. When robots fail, behave unexpectedly, or need to be improved, engineers rely on data to understand what actually happened.

At Foxglove, we build the observability, visualization, and data infrastructure that makes that possible. Our tools are used by robotics and autonomous systems teams to ingest, store, query, replay, and analyze massive volumes of multimodal sensor data from live systems and from production fleets.

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.
Key Responsibilities

• 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 search over petabyte-scale robotics data using vector databases and embedding models

• Designing evaluation and training pipelines so the team can iterate quickly on model performance

• Ingesting and serving massive volumes of sensor data through batch and realtime pipelines

• Developing product features to help robotics engineers organize, search over, and serve their data for training ML models

• Making real build-vs-buy decisions on cloud architecture across multi-cloud environments (GCP, AWS, Azure)

• Collaborating with product engineers to ship features that go directly to customers building robotics and autonomous systems

Our Technical Stack

• Rust, TypeScript, PostgreSQL

• Kubernetes

• GCP, Azure, and AWS

• Agentic coding tools (Claude Code / Cursor)

What We're Looking For

• Bachelor's or Master's degree in Computer Science, Robotics, or a related field (recent graduates or graduating in 2026)

• Hands-on ML experience — through internships, research, or academic projects — with a bias toward applied/production work over research

• Familiarity with ML frameworks and inference tooling (e.g., PyTorch, TorchServe, vLLM, Triton, or similar)

• Experience writing software in Python, Rust, C++, or TypeScript

• Exposure to distributed systems concepts, cloud infrastructure (GCP, AWS, Azure), or data-intensive applications

• Familiarity with vector databases, embedding models, or retrieval systems

• Familiarity with SQL databases and an interest in query engines, big data storage and retrieval, and data-intensive systems

• Passion for building technical tools where engineers are the primary users

• Excellent written and verbal communication skills

• Eagerness to learn and thrive in a fast-paced, small team environment

• A mindset that considers customer impact when making technical decisions

Bonus Points

• Experience with model optimization techniques — quantization, distillation, mixed precision, or TensorRT

• Familiarity with fine-tuning or domain adaptation for vision, language, or multimodal models

• Experience with sensor data pipelines (lidar, camera, IMU, etc.) or autonomous vehicle software stacks

• Published robotics or ML research, or contributions to open-source projects

• Experience with Spark/Databricks or large-scale data processing

• Exposure to infrastructure-as-code (Terraform), Kubernetes, or cloud provider administration

• Interesting personal projects that solved a real problem

What We Offer

• $300 monthly budget towards commuter benefits or building your personal workspace (remote only)

• Competitive equity grant in a Series B company

• Medical, Dental, Vision, and Term Life insurance coverage at 100% for employees and 75% for dependents

• 401(k) matching up to 4%

• 4 weeks vacation, plus holidays and winter break

• All expenses paid company off-sites 1–2× per year

Why Join Us

• Impact: Own growth at a fast-growing, high-leverage moment for the company

• Mission: Accelerate the development of the next generation of robotics and embodied AI

• Team: Work with world-class engineers, designers, and researchers passionate about open-source and developer tools

• Ownership: Drive initiatives end-to-end, with high autonomy and visibility

[11:24 AM]

Claude combined the JD of the SWE new grad with the information Eric wanted for the MLE new grad and then I just added the same "What we're looking for, bonus points, what we offer, and why join us"

Why Join Us

• Impact: Own growth at a fast-growing, high-leverage moment for the company.

• Mission: Accelerate the development of the next generation of robotics and embodied AI.

• Team: Work with world-class engineers, designers, and researchers passionate about open-source and developer tools.

• Ownership: Drive initiatives end-to-end, with high autonomy and visibility.