Mechanical Design Engineer: Robotics Hardware Engineering

Meta Meta · Big Tech · Redmond, WA

Meta is seeking a Mechanical Design Engineer for their Robotics Hardware team. This role involves designing and developing complex robotics, focusing on ergonomics, performance, reliability, and usability while maintaining safety and quality standards. Responsibilities include concept development, analytical modeling, prototype design, construction, and testing in a high-ambiguity environment. The team builds hardware for data collection and testing.

What you'd actually do

  1. Design and analysis problems for prototype robotics structures, mechanisms, power transmissions, and systems integration while balancing ergonomics, performance, reliability, weight, and maintainability
  2. Working with internal/external partners to support part fabrication and robot builds, fixtures and assembly tooling design, assembly procedures
  3. Build subsystem test fixtures, design tests, create test plans, perform tests, measure and analyze data, and refine design assumptions
  4. Work closely with a cross-functional team of engineers (EE, SW, Firmware) to deliver complete technical solutions
  5. Troubleshooting root-cause of mechanical failures, implementing improved designs, testing effectiveness of change

Skills

Required

  • 5+ years experience in Mechanical Design Engineering
  • experience in Machine Design
  • BS degree or equivalent experience in Mechanical Engineering or a related field
  • Experience designing complex electromechanical assemblies (e.g. robotics, automotive, aerospace, industrial automation)
  • Experience with SOLIDWORKS, Siemens NX or similar CAD tools
  • Experience with prototyping manufacturing processes and materials
  • Experience managing time-sensitive projects through to completion while balancing evolving priorities and a broad range of stakeholders
  • Experience in tolerance analysis, geometric dimensioning and tolerancing (GD&T)
  • Experience in Finite Element Analysis (FEA)
  • Experience in Robotics, Humanoids, Automation
  • Experience driving and leading projects from cradle to grave

What the JD emphasized

  • high ambiguity
  • full system requirements are seldom known
  • building hardware that enables learning through data collection and testing
  • evolving priorities