Hands-On Mechanical Design Engineer — Robotics Hardware

Gradient Robotics

San Francisco (CA)

On-site

USD 90,000 - 120,000

Full time

14 days+

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Job summary

Gradient Robotics is seeking a Mechanical Engineer to own subassemblies from first sketch to validated hardware. This hands-on role requires designing a part, performing hand calcs and basic FEA, fabricating, and testing on the robot, with rapid iteration on failures within the same week.

You will work closely with a small team in San Francisco, on-site five days a week (six during crunch times), building components that scale AI infrastructure worldwide.

Qualifications

  • 1-4 years of mechanical design experience (exceptional new grads with strong project or internship work are welcome)
  • Solid fundamentals: statics, materials, tolerance analysis, fasteners, and basic FEA
  • Experience building things: student teams, products that shipped, prototypes that worked
  • Hands-on machining experience: we have some really cool machines, and as a small team, engineers do need to make their own parts at times
  • Able to work on-site in San Francisco 5 days/week (6 days/week if needed during crunch time), embedded in the team

Responsibilities

  • Own a subassembly and its parts through design, hand calcs, FEA, fabrication, assembly, and validation
  • Own the supporting analysis: hand calcs, tolerance stack-ups, fastener and material selection, and basic FEA
  • Build, assemble, and test your own parts on test fixtures and on the robot
  • Iterate fast: turn feedback from a failed test into a revised part the same week

Skills

Statics
Materials
Tolerance analysis
Fasteners
Basic FEA
Hand calcs
Machining
On-site work

Tools

Fusion 360

Job description

Gradient Robotics is seeking a Mechanical Engineer to own subassemblies from first sketch to validated hardware. This hands-on role requires designing a part, performing hand calcs and basic FEA, fabricating, and testing on the robot, with rapid iteration on failures within the same week.

You will work closely with a small team in San Francisco, on-site five days a week (six during crunch times), building components that scale AI infrastructure worldwide.

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