Manufacturing Quality Engineer BotQ

Figure•San Jose, CA

4d•$150,000 - $250,000

About The Position

Figure is an AI robotics company developing autonomous, general-purpose humanoid robots for home and commercial markets. The company is headquartered in San Jose, California, and aims to build humanoid robots with human-level intelligence. The Manufacturing Quality Engineer owns quality for assigned in-house assembly lines, supports quality planning and readiness from new product introduction through production, and leads investigation and resolution of failures in the field and during remanufacturing. The role also contributes to the manufacturing quality management system, partners with Supplier Quality, and mentors quality engineers and technicians. This is a full-time position with a US base salary range of $150,000 to $250,000 per year. Pay may vary based on job-related knowledge, skills, and experience. Total compensation may include additional components or benefits depending on the role; details are shared if an offer is extended.

Requirements

At least 7 years of quality engineering experience in high-volume electromechanical manufacturing, such as automotive, consumer electronics, or robotics.
Bachelor’s degree in Mechanical, Electrical, Manufacturing, or Mechatronics Engineering, or a related technical field.
Hands-on experience authoring PFMEAs and control plans and carrying them from new product introduction into production.
Experience with structured problem-solving methods, including 8D, 5-Why, fishbone analysis, and formal corrective action processes.
Knowledge of GD&T and ability to interpret complex technical drawings.
Experience with statistical analysis and SPC using tools such as JMP or Minitab, and ability to build dashboards from inspection and test data.
Experience with robotic systems, automation, or complex electromechanical assemblies.
Track record of working on the production floor directly with operators, manufacturing engineering, and design teams.

Nice To Haves

Battery pack, actuator, or drivetrain assembly experience.
Field failure analysis, warranty, or remanufacturing quality experience.
Knowledge of ISO 9001 or IATF 16949 standards.
Six Sigma Green Belt or Black Belt certification.
Hands-on experience with automated inspection systems, such as CMM or vision systems.
Experience building a quality management system from the ground up.
CATIA V6 experience.

Responsibilities

Own quality on assigned in-house assembly lines, such as battery pack assembly and final robot assembly.
Define control plans, in-process checks, and end-of-line checks, and drive them toward automated inspection and data capture by the start of mass production.
Monitor first-pass yield and defect Paretos, apply statistical process control where useful, and lead the daily quality response on the line.
Lead manufacturing line audits covering processes, specifications, tooling and gauges, data recording, and operator training.
Represent quality on next-generation robot builds by reviewing process flows with Manufacturing Engineering and authoring and maintaining PFMEAs and control plans ahead of each build phase.
Translate DFMEA severity and safety-critical classifications into process controls and provide design teams with feedback on design gaps.
Define quality line-readiness criteria and sign off on readiness from prototype builds through start of production.
Own failure analysis for field returns and remanufactured units, including structured failure coding, teardown, and root-cause analysis using 8D, 5-Why, and fishbone analysis.
Connect field data to corrective actions in production and design.
Drive DOA and return resolution with remanufacturing and commercial teams.
Help build the manufacturing quality management system, including internal audits, corrective and preventive action, deviation handling, equipment qualification, and training standards.
Partner with Supplier Quality on incoming inspection and supplier corrective actions for components used on production lines.
Mentor quality engineers and technicians and promote structured problem solving across Production, Manufacturing, and Quality.