Anvil Robotics

Senior Software Engineer, Data Collection Systems

San Francisco, CA · Senior · Full-time

Sponsorship not specifiedDetected 6 days ago

AlgorithmsMachine LearningRoboticsElectrical EngineeringSensorsResearchPipeline Integrity

About the role

Devkits are the wedge, not the business.
The handheld data collection system is the front end of that strategy: the instrument that turns real world tasks into training data at scale.
Trusted with real technical judgment calls across team boundaries without formal authority over any of those teams.

The researchers who define this field run their experiments on our hardware, and many of them bought it with their own money.
pose tracking, model training, SoC/chip integration, and industrial design.
Each piece works, but nobody currently owns making them work together as one product a customer can actually pick up and use.
Acting as the systems and product engineer across specialist teams, including pose tracking, model training, SoC/chip, and industrial design.
Building real infrastructure for parts of the system that do not have it yet, including turning the model team's scripts into something repeatable.
is the person other engineers, including those in pose tracking, model training, SoC/chip, and industrial design, go to when something is not fitting together.

You have done systems or product integration work for a robotic or perception based product before.
You have been the person who made disparate technical pieces (hardware, perception, software, sometimes ML) work together into something a real user relied on.
You have genuine, provable depth in at least one of the following, along with familiarity with several of the others:
Embedded application development: you have gotten real applications built, deployed, and running reliably on constrained or embedded hardware
Master's degree in robotics, computer science, electrical engineering, or a related field - or a bachelor's with equivalent hands-on depth.
A PhD is not required
you have gotten real applications built, deployed, and running reliably on constrained or embedded hardware

Has personally used the device to collect data end to end at least once.
ML workflow, training, and deployment engineering
Physical AI and robot learning deployment, for example VLA style policies, getting a trained model to actually make a robot do something

That volume has earned us a custom force sensing actuator partnership with major actuator OEMs, and the install base becomes both the distribution channel for our next generation robots and a platform for the data and software layers above them.

This listing is sourced directly from Anvil Robotics's careers page and normalized into a canonical job model.