Data Infrastructure Engineer

About the team

Droyd builds autonomous robotic systems that take on repetitive manual work in real environments. Our robots generate high-rate video, telemetry, and demonstration data every time they move — and that data is what trains our models.

Our software team builds the systems that connect robots to learning. Data infrastructure sits at the center of that loop: what gets captured, how it moves, and how fast it becomes training signal. This work runs on real machines, not benchmarks.

About the role

As a Staff Software Engineer on data infrastructure at Droyd, you'll own the pipelines that carry data from robot to model. You'll architect ingestion from edge devices, streaming transport, storage, and retrieval — and make fleet data immediately usable for training and evaluation.

You'll work in person with a small, senior team across robotics, ML, and hardware. Your work will ship directly to deployed systems.

This role is based in San Francisco, CA. We're an in-person company. We build faster that way.

• In this role, you'll
• Architect, build, and maintain highly-available data pipelines for robot video, telemetry, and demonstration data
• Own the path from robot to training set: edge ingestion, MoQ/WebTransport streaming, storage, indexing, and retrieval
• Work with ML and robotics engineers to make fleet data immediately usable for training and evaluation
• Improve throughput, reliability, and cost across the full data path
• Build tooling that lets the team find, inspect, and trust the data
• Help set technical direction for data and infrastructure as the fleet scales
• We're looking for someone who
• Has 5+ years of software development experience
• Has hands-on experience architecting and optimizing large-scale data pipelines
• Is proficient in Rust, Go, or Python — Rust is a big plus
• Has a strong sense of ownership and can drive complex systems end to end
• Communicates clearly and works well with ML, robotics, and hardware engineers