Data Infrastructure Engineer
Droyd · On-site
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Job details
- Work model
- On-site
- Salary
- Not listed by source
- Location
- San Francisco, CA
What the role asks for
What you'd do
- 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
What they're asking for
- Has 5+ years of software development experienceExperience
- Has hands-on experience architecting and optimizing large-scale data pipelinesSkill
- Is proficient in Rust, Go, or Python - Rust is a big plusSkill
- Has a strong sense of ownership and can drive complex systems end to endSkill
- Communicates clearly and works well with ML, robotics, and hardware engineersSkill
- Bonus: experience with streaming video, telemetry-heavy systems, or robotics/edge dataSkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
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 - Bonus: experience with streaming video, telemetry-heavy systems, or robotics/edge data About Droyd Droyd builds autonomous robotic systems to automate manual work for enterprises. We design the hardware, write the control stack, collect our own data, and train models that run under real-world constraints. If we do this right, robots stop being demos and start being tools people rely on every day. Join us and help build systems that actually ship.
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