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Motivo

AI-powered analytics optimizing IC design yield

Electro-Mechanical Technician

Hardware Systems IntegrationConfirmed live in the last 24 hours
Full-timeRancho Dominguez, Compton, CA, USAIn-person

About the Job

Requirements

  • An interest in both electrical and mechanical work, with roughly 60% electrical and 40% mechanical emphasis.
  • A solid understanding of electricity, including volts, amps, fuses, wire, AC versus DC, and voltmeters.
  • A solid understanding of mechanical systems, including how engines work and the ability to take apart and reassemble equipment.
  • Interest and ability to work on both large diesel engines and small 3D-printed plastic enclosures with sensitive electronics and wiring.
  • Professionalism, including consistently arriving on time and wearing appropriate clothing.
  • One to three years of professional experience.
  • An Associate degree in Engineering Technology or similar, a Professional or Occupational Certificate in Technology or similar, or directly applicable professional experience.

Responsibilities

  • Work on projects involving both electrical and mechanical systems.

Desired Qualifications

  • Electrical harness build, debugging, or repair experience, especially with automotive, racing, military, or aerospace harnesses.
  • Experience with electrical crimping tools, crimp-style components, and connector contacts.
  • Exposure to welding.
  • Exposure to electronics soldering.
  • Exposure to metal fabrication environments and tools.
  • Exposure to machine shop environments and tools, including mills, lathes, and grinders.
  • Exposure to reading schematics, circuit analysis, and debugging techniques.
  • Exposure to electronics troubleshooting tools, including oscilloscopes, function generators, and digital multimeters.

About the Company

Motivo

AI-powered analytics optimizing IC design yield

Motivo provides AI-driven analytics for the semiconductor design and manufacturing process. Its software analyzes the full chip workflow from RTL to layout using a proprietary learning-on-graph approach (M-Graph) to automatically extract data-driven features. Its modules include M-DVP for accelerating design validation, M-TCO for faster timing convergence, and M-OPT for improving manufacturing yield. The system offers explainable AI to identify root causes of yield problems and prescribes actionable steps, helping teams reduce design validation time and increase yield. Motivo differentiates itself with end-to-end, data-centric optimization that spans design and manufacturing, grounded in graph-based learning and an emphasis on explainability. The company aims to help fabless design houses and other semiconductor firms shorten development cycles and lower costs when designing and ramping up new chips.

Company size
1-10
Company stage
Series A
Total funding
$20.5M
Headquarters
Palo Alto, CA
Founded
2015

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