Senior Reliability Engineer

About the Role

Agility Robotics is at the forefront of humanoid robotics, redefining how robots interact with and navigate the human world. Our cutting-edge robots rely on advanced mechatronic systems—integrating precision actuators, high-performance motor controllers, multi-axis force/torque sensors, high-density PCBAs, cable harnesses, structural limbs, and dynamic end effectors—to execute complex tasks in demanding environments.

We are seeking a Senior Reliability Engineer with 5–8+ years of hands-on experience in mechatronics and electromechanical systems to join our team in the San Francisco Bay Area. In this hybrid role, you will be the core technical owner for the reliability of integrated humanoid drive systems and robotic actuation sub-assemblies. You will partner directly with mechatronics design, controls, embedded software, and manufacturing teams to drive reliability validation, lead multi-physics failure analyses, and build robust lifetime models for highly dynamic robotic hardware.

About the Work

Mechatronic Reliability Planning & DfR Integration

• Implement Design for Reliability (DfR) methodologies (DFMEA, FTA, component derating) across complex mechatronic loops, including drive trains, harmonic gearboxes, BLDC motors, encoder feedback systems, and dynamic wire harnesses.
• Establish reliability targets, duty-cycle profiles, and environmental/mechanical stress acceptance criteria for actuators, sensors, power electronics, and end effectors.
• Collaborate with control systems and mechatronics design teams to evaluate the reliability impact of control algorithms, dynamic braking, overload torque conditions, and thermal throttling regimes.

Advanced Mechatronic Testing & Lifetime Validation

• Design, build, and execute multi-axis accelerated stress testing setups, including HALT, HASS, dynamic load cycling, thermal shock, vibration, and ingress protection (IP) validation.
• Develop custom dynamic test rigs to simulate real-world humanoid duty cycles (e.g., continuous walking, heavy payload lifting, impulse landing impacts, high-frequency oscillatory motion).
• Apply statistical reliability tools (Weibull analysis, ALT/CALT models) and multi-physics degradation models (e.g., Coffin-Manson, Arrhenius, bearing/gear fatigue modeling) to predict drive system lifetime under dynamic field loads.

Failure Analysis & Closed-Loop Improvement

• Lead cross-functional Root Cause Analysis (RCA) for complex mechatronic failures across mechanical wear (gears, bearings), electrical degradation (FET switching, PCBA thermal fatigue), and signal/sensor degradation (encoder slip, harness flex failure).
• Translate field telemetry, torque/temperature logs, and test bench failure data into actionable design revisions for next-generation humanoid architectures.

About You

Experience

• Minimum of 5 to 8+ years of experience in reliability engineering for complex hardware systems
• Strong preference for candidates with experience in robotics, autonomous vehicles, aerospace, or other high-reliability industries

Technical Expertise

• Strong understanding of mechatronic systems integrating mechanical structures, electronics, actuators, sensors, and control hardware.
• Demonstrated experience with reliability engineering principles including Design for Reliability, DFMEA/FMEA, accelerated-life testing, reliability demonstration, reliability growth, component derating, and physics-of-failure analysis.
• Experience developing or executing environmental and durability tests such as vibration, thermal cycling, mechanical fatigue, humidity, HALT, or accelerated endurance testing.
• Familiarity with statistical reliability methods including Weibull analysis, success-run testing, confidence bounds, and accelerated-life modeling.
• Working knowledge of fatigue and life-prediction methods such as Coffin-Manson, stress-life, strain-life, Miner’s rule, or equivalent approaches.
• Understanding of common mechanical, electrical, and electromechanical failure mechanisms.
• Ability to interpret mechanical drawings, electrical schematics, test data, material specifications, and supplier qualification reports.

Tools & Analysis Methods

• Experience using reliability, statistical, simulation, and engineering analysis tools to support reliability assessments and decision-making.
• Ability to analyze life data, accelerated-test results, failure distributions, and reliability-growth trends.
• Experience applying physics-based simulation or analytical methods to evaluate mechanical, thermal, vibration, fatigue, or electronics reliability risks.
• Proficiency with data-analysis and scripting environments used for engineering analysis is preferred.
• Ability to learn and effectively use new reliability and engineering software tools as needed.

Skills

• Strong analytical and structured problem-solving ability.
• Ability to connect observed failures and test results to underlying physical failure mechanisms.
• Ability to independently develop reliability analyses and validation approaches.
• Strong written and verbal communication skills.
• Ability to communicate reliability risk, uncertainty, and recommendations to both technical and non-technical stakeholders.
• Effective collaboration across mechanical, electrical, systems, test, manufacturing, quality, and supplier organizations.
• Ability to operate effectively in a fast-moving product-development environment where designs and requirements continue to mature.

Education

• Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Mechatronics, Materials Science, Reliability Engineering, or a related technical field.
• Master’s degree or PhD is a plus.
  
  

Location

• This is a hybrid position based out of Fremont, CA office.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: job-related knowledge, skills, and experience. Agility Robotics is a multi-state employer and this salary range may not reflect positions who work in other locations. These ranges may be modified in the future.