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# Robotics Hardware & Data Engineer

- **Company:** Flowserve Holdings, Inc.
- **Location:** Redwood City, CA, United States
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Big Data, Computer Engineering, Software Debugging, Embedded Software, Hardware Design, Hardware Interface Design, Machine Learning, Signal Processing, Spatial Data Infrastructures, Build Management, Low Latency, Data Pipelines
- **Published:** November 14, 2026
- **Apply:** https://www.careerbuilder.com/job-details/robotics-hardware-data-engineer-redwood-city-ca--f85ba9ab-e45b-49a2-a273-59c1ba5373b0

## About the Role

Robotics, Computer Engineering, Training/Teaching, Spatial Data, Artificial Intelligence (AI), Robotics, Data Collection, Computer Engineering, Hardware Design, Motor Control Systems, * Background in mechanical/mechatronics engineering, robotics, or a closely related field.

 * Hands-on experience with motors, robotic control, and signal processing.
 * Familiarity with machine learning and robot learning - you understand how data becomes a trained policy.
 * Comfort working across hardware and software: embedded systems, real-time control, and data pipelines.
 * A builder's instinct: you like making physical systems work reliably in the real world.

Nice to have:

 * Experience with teleoperation systems or large-scale robot data collection.
 * Familiarity with the robot learning research community (e.g. CoRL) and modern imitation/RL approaches.
 * Experience designing data schemas or catalogs for ML training.

## Description

We're looking for a Robotics Hardware / Data Engineer to design the hardware and software interfaces that power robot teleoperation and large-scale data collection. You'll own the systems that let human operators control robots and that turn every session into clean, high-fidelity training data. This is a hands-on role spanning mechatronics, embedded software, and ML data pipelines - ideal for someone who's equally comfortable with a motor driver and a training loop.

 * Design and build hardware interfaces for robot teleoperation - mapping human input to robot control in real time.
 * Develop data-collection systems that record synchronized, high-quality sensor, actuation, and video streams for downstream robot learning.
 * Work across the stack: motor control, signal processing, and low-latency communication between operator hardware and robots.
 * Build the tooling and pipelines that validate, clean, and structure collected data for ML training.
 * Partner across engineering, operations and research teams to make sure the data we capture matches what models actually need, and feed learnings back into hardware and catalog design.
 * Prototype quickly, debug real hardware, and iterate on rigs, controllers, and capture setups.