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Frontier AI is expanding into physical labs and needs a Software Engineer on Robotics to bridge data systems with customer infra. You’ll build configurable pipelines, support per-client schemas, and deliver scalable data moves at petabyte scale.
Prior robotics experience isn’t required; this is a backend/data engineering role focused on pipelines, formats, and storage. You’ll work with Python/Go/Rust on AWS/GCP, own end-to-end data deliveries, and collaborate with customers to define bespoke
Frontier AI is going physical, and the labs building it are bottlenecked on one thing: high-quality data from the real world. We pair operational scale with the specialized engineering that physical-world data demands.
As a Software Engineer on Robotics, you'll sit between our data systems and our customers' infrastructure. Every frontier lab wants something different: container format, schema, fields, and quality requirements. You'll build infrastructure general enough that a new customer becomes a quick configuration, and you'll work directly with customer engineering teams on bespoke requests, feeding what you learn into scalable platform architecture decisions. An example might be modifying the segmentation model derived from a customer request for stricter filtering on hands being in frame and building this into a configurable pipeline feature.
Prior robotics experience is not required. This is a backend and data engineering role at its core, developing pipelines, formats, and storage methods. If you've built high-volume data infrastructure anywhere and want depth in robotics data, working directly with the engineers and researchers at the labs and robotics companies building physical AI, this role is for you.
Own the reusable infrastructure behind robotics data deliveries: the processing, packaging, and delivery systems
Format and transform datasets to per-client specification: MCAP and other container formats, custom schemas, field mappings, metadata, and versioning
Work directly with customer engineering teams to scope and build bespoke schemas, custom fields, and one-off transforms where requirements are custom
Build and operate the pipelines that move data from our systems into customer storage reliably at petabyte scale
Partner with operations and product to turn evolving requirements into shipped data deliveries, and prototype quickly when a new data type or customer arrives
Build automated validation techniques
Strong backend and data engineering fundamentals in a modern language (Python, Go, Rust) and comfort operating production systems on AWS and GCP
Experience building and owning high-volume data pipelines, not just contributing to them
Experience with large binary formats, streaming ingestion, distributed batch processing, and object storage economics
Customer-facing instincts: you can lead a technical conversation, ask the right questions, and push back when a request is unreasonable
Comfort working through ambiguity and shipping iteratively with a product team, where requirements evolve with the customers and data types
Experience with robotics/AV data formats and tooling such as MCAP, ROS, protobuf, Foxglove
Prior work on data engines, pipelines, or delivery for multimodal data
Multi-sensor data experience across video, depth, inertial, and audio, including calibration and synchronization
Forward-deployed, solutions, or delivery engineering experience at a data or infrastructure company
Computer vision or multimodal ML exposure: detection, tracking, or VLM-based labeling and QC