Staff Reliability Engineer

Bedrock Robotics
San Francisco, CA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source

Tech stack

Data Analysis Failure Mode Effects Analysis Python (Programming Language) Minitab Reliability Engineering Software Reliability Testing Test Data Windchill Test Scripts Reliability of Systems Statistics Packages Data Pipelines

Job description

As a Staff Reliability Engineer, you will own hardware reliability for our next-generation autonomous construction machines. You will define and drive the reliability engineering programs across compute, sensors, cleaning, power, actuation, and supporting subsystems - establishing reliability requirements and budgets, leading Design FMEAs (DFMEA) and Fault Tree Analysis (FTA), building reliability models and test programs, and closing the loop from field failures back into design. Working closely with mechanical, electrical, software, manufacturing, quality, supply chain, and field teams, you will translate reliability goals into design, test, and process decisions that keep machines running in demanding real-world environments - from vibration and shock, to dust, debris, thermal extremes, and weather exposure.

What You’ll Do:

  • Reliability Program Ownership: Define and own the hardware reliability strategy, requirements, and budgets (reliability/availability targets, MTBF/MTBUR goals, duty cycles, mission profiles) for autonomy upfit hardware across the vehicle platform.
  • DFMEA Leadership: Plan and facilitate Design FMEAs across mechanical, electrical, and electromechanical subsystems - identifying failure modes, effects, and causes; scoring severity/occurrence/detection; prioritizing with RPN/Action Priority; and driving design and test actions to closure.
  • Fault Tree Analysis (FTA): Build and maintain fault trees for safety-critical and availability-critical functions; perform qualitative and quantitative FTA, identify minimal cut sets and single points of failure, and link top-level undesired events to design, redundancy, and verification requirements.
  • Reliability Modeling & Prediction: Develop reliability block diagrams, reliability allocations, and predictions; perform Weibull and life-data analysis, reliability growth tracking, and worst-case/derating analysis to forecast field performance and inform design tradeoffs.
  • Reliability Testing: Define and execute HALT/HASS, accelerated life testing (ALT), and environmental/durability test programs (vibration, shock, thermal cycling, dust/water ingress, corrosion); set test-to-failure margins and design ongoing stress screens.
  • Field Failure Analysis: Stand up and run a Failure Reporting, Analysis, and Corrective Action System; lead root-cause investigations (8D, 5-Whys, fishbone, fault isolation) and drive corrective/preventive actions from field and test data into design and process.
  • Design for Reliability (DfR): Embed reliability into design and milestone reviews - derating, redundancy, tolerance stack-up, thermal and vibration margin, connector/harness reliability, ingress protection - and gate designs at NPI stages.
  • Supplier & Component Reliability: Partner with supply chain and vendors to qualify components and suppliers, define reliability acceptance criteria, review supplier reliability data, and manage derating, qualification, and obsolescence risk.
  • Reliability Data & Tooling: Build reliability data pipelines and dashboards from warranty/field returns, machine telemetry, and test data; apply statistical methods to quantify reliability and surface emerging failure trends early.
  • Cross-Functional Collaboration: Partner with electrical, mechanical, software, manufacturing, and field teams during bring-up, validation, and deployment to turn reliability findings into actionable design, process, and test changes.
  • Documentation & Standards: Maintain reliability deliverables (DFMEA and FTA records, reliability plans, prediction models, test reports, FRACAS records) and develop best-practice reliability processes that support predictability, transparency, and quality.

Requirements

  • Education: Bachelor’s degree in Mechanical or Electrical Engineering, Reliability Engineering, Physics, Mechatronics, or a related field, or equivalent experience.
  • Experience: 10+ years in hardware reliability engineering for vehicles, heavy machinery, robotics, automotive, aerospace, or industrial equipment.
  • Reliability Methods: Deep, hands-on expertise leading DFMEA and FTA, plus reliability prediction/modeling, accelerated and life testing (HALT/HASS, ALT), and structured root-cause analysis / FRACAS.
  • Tools: Strong working knowledge of reliability and statistical tools (e.g., ReliaSoft Weibull++/BlockSim, Windchill Quality/Relex, Minitab, Python or R); familiarity with PDM/PLM systems a plus.

About the company

Join the team bringing advanced autonomy to the built world

At Bedrock, we’re moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we’re deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we’re working quickly to close the gap between America’s surging demand for housing, data centers, manufacturing hubs, and the construction industry’s growing labor shortage.

This is where algorithms meet steel-toed boots. You’ll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can’t touch. If you’re ready to apply cutting-edge technology to solve meaningful problems alongside a talented team-we’d love to have you join us.

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