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.
We're looking for a senior engineer who can operate at the intersection of large-scale data infrastructure and applied ML. You'll design and operate the pipelines that ingest, store, search and curate petabyte-scale multimodal sensor data, and build the retrieval and ML systems that sit on top of it — semantic search, embeddings, inference at scale — to turn that data into something developers can actually explore, mine, and learn from.
This is a hands-on, application-driven role. You'll own real product and architecture decisions, not implement someone else's design, and what you build ships to customers.
Our technical stack includes:
Node.js (TypeScript) and Rust for services
PostgreSQL and vector databases
Model serving
Managed Kubernetes on GCP, with customer deployments across AWS and Azure
Design and build search and curation systems for enabling ML engineer customers to inspect and utilize data
Build low-latency, random-access playback systems that let users explore live or recorded data across devices, time ranges, and sensor modalities
Stand up semantic and hybrid search over multimodal robotics data (video, point clouds, images, timeseries) — including vector database integrations and embedding application pipelines
Deploy and operate inference infrastructure for production ML workloads: model serving, scaling, latency and cost optimization
Architect and maintain multi-cloud deployments across GCP, AWS, and Azure, including components that run inside customer-managed environments
Partner with product engineers to ship application-driven features to developers building the cutting edge of robotics and physical AI — not prototype experiments
Make thoughtful build vs. buy calls: identify the right off-the-shelf ML and data solutions and adapt them for production
8+ years of professional experience writing high-performance production software
Strong backend engineering experience, providing high performance APIs to consumers
Hands-on experience with production ML infrastructure — cloud inference, model serving frameworks (TorchServe, vLLM, Triton), and cost/latency optimization
Experience with retrieval systems: vector databases and text/image embedding models
Solid distributed systems fundamentals, including SQL query planning and scaling data workloads
A bias toward application and product impact over research — you're energized by shipping things that work, not writing papers
Ability to thrive in a fast-paced, small-team environment with real ownership and loosely defined scope
Considers customer impact when making technical decisions
Excellent written and verbal communication — you can explain data and systems tradeoffs to non-specialist engineers
Robotics or AV experience, especially with AV data or sim infrastructure
Significant experience building REST APIs in TypeScript, Go, and/or Rust
Experience deploying and operating multi-cloud data systems (GCP/AWS/Azure) and familiarity with cloud-native data infra (S3, BigQuery, Redshift, etc.)
Strong background in observability and performance monitoring for data systems
Real-time analytics or multimodal sensor processing experience
Experience with data mining or hybrid search workflows in robotics, AV, or physical AI contexts
Experience building ML tooling, data management, and evaluation frameworks from scratch
Infrastructure management (IaC/Terraform, Kubernetes, cloud security)
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.
foxglove