Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA.
Figure’s Hardware REL team is looking for a motivated Hardware Test Engineering Intern for an extended internship of 8–12 months. You will help design, build, and validate electromechanical test stations to evaluate the functionality, performance, and reliability of humanoid robot hardware. This hands-on role combines mechanical fixtures, electrical hardware, sensors, actuators, and motion control. You will collaborate with mechanical, electrical, and software engineers to solve practical integration challenges in a fast-paced engineering environment.
Responsibilities:
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Design and build test fixtures and scalable test stations for functional, performance, and reliability testing of robotic components and subassemblies.
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Integrate mechanical fixtures, electrical wiring, data acquisition systems, power supplies, sensors, actuators, and controllers into complete test setups.
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Support the development of test procedures and pass/fail criteria based on hardware design requirements and expected operating conditions.
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Develop test sequences and modify test configurations to control test equipment, automate test operation, and collect and analyze measurement data.
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Perform test station bring-up and qualification, including checking measurement accuracy, repeatability, data capture, and safety interlocks.
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Execute tests, monitor hardware behavior, and document results, anomalies, and failures.
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Troubleshoot test setups and support root cause investigations across mechanical, electrical, and software interfaces.
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Create and maintain fixture drawings, electrical schematics, wiring diagrams, bills of materials, and test documentation.
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Collaborate with cross-functional teams to improve test coverage, station reliability, and testing efficiency.
Requirements:
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Pursuing a degree in Mechanical Engineering, Electrical Engineering, Robotics, Mechatronics, or a related engineering field, with at least two years completed by the start of the internship.
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Availability for an 8–12-month internship with in-office collaboration five days per week.
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A portfolio, website, or project examples demonstrating relevant hands-on work and your individual contributions.
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Hands-on experience designing, assembling, and testing mechanical or electromechanical systems through coursework, personal projects, internships, or engineering teams.
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Familiarity with basic electrical circuits, wiring, sensors, and laboratory equipment such as multimeters, oscilloscopes, or bench power supplies.
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Basic programming experience in Python or a similar language for equipment control, test automation, or data analysis, and familiarity with Git.
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Ability to interpret test data, troubleshoot problems systematically, and document findings clearly.
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Strong attention to detail and the ability to collaborate effectively across engineering disciplines.
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Interest in robotics, hardware testing, and reliability engineering.
Bonus Qualifications:
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Experience with mechanical CAD tools, particularly CATIA V6, or electrical schematic design tools.
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Experience with fixture design, 3D printing, machining, soldering, or other prototyping and fabrication methods.
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Experience integrating motors, motor controllers, load cells, encoders, thermocouples, or other test instrumentation.
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Familiarity with data acquisition systems and communication interfaces such as CAN, serial, USB, or Ethernet.
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Experience with Python-based test automation, data visualization, or Linux.
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Familiarity with calibration, measurement uncertainty, gauge repeatability and reproducibility (GR&R), or test-station qualification.
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Exposure to reliability testing, accelerated life testing, manufacturing testing, or failure analysis.
The US base pay range for this full-time position is $40.00 to $45.00 per hour.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.