Senior​/System Reliability and Risk Engineer

Senior/Staff System Reliability and Risk Engineer

Mountain View, CA

Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion. The company focuses on short‑haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world’s first fully driverless commercial transportation service with Walmart. Gatik's Class 3‑7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation.

The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom‑built to transport freight safely and efficiently between pick‑up and drop‑off locations on the middle mile. With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all‑encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations.

We’re seeking a Reliability and Risk Engineer to lead efforts in analyzing, predicting, and improving the reliability and safety of our autonomous trucking systems. You’ll work across hardware, software, and systems teams to identify failure modes, assess risks, and drive data‑informed design decisions using advanced statistical methods.

This role is onsite 5 days a week at our Mountain View, CA or Fort Worth, TX office!

• Develop and execute reliability strategies for components and systems
• Perform FMEA, FMEDA, Weibull, and fault tree analyses
• Define reliability metrics (MTBF, MTTR, failure rates) and lead root cause investigations
• Conduct accelerated life testing and assess design performance statistically
• Apply probabilistic risk methods like Monte Carlo simulations and Bayesian inference
• Develop models to evaluate risk across system behaviors and scenarios
• Support safety case development and compliance with ISO 26262, ISO 21448, UL4600
• Analyze validation and fleet data to detect trends, failure precursors, and degradation
• Collaborate on predictive maintenance tools, dashboards, and fault detection models
• Work closely with cross‑functional teams to integrate reliability into all development stages
• Support incident investigations, certification, and continuous improvement processes

• Master’s or Ph in MechE, EE, Systems, Reliability, Stats/Math, or related field
• 5+ years in reliability engineering or risk analysis in autonomous or safety‑critical systems
• Strong skills in Python, R, MATLAB, or similar for statistical modeling
• Familiarity with standards like ISO 26262, MIL‑STD‑882, IEC 61508
• Deep understanding of risk and reliability methods (e.g., hazard rates, survival analysis)
• Experience working with large datasets to drive insights
• Strong communicator with excellent organizational and project management skills

• Experience with ML for reliability prediction or anomaly detection
• Background in predictive analytics for AV or robotics
• Familiarity with AV safety certification and regulatory engagement

Salary Range: $160,000 – $240,000

Founded in 2017 by experts in autonomous vehicle technology, Gatik has rapidly expanded its presence to Mountain View, Dallas‑Fort Worth, Arkansas, and Toronto. As the first and only company to achieve fully driverless middle‑mile commercial deliveries, Gatik holds a unique and defensible position in the AV industry, with a clear trajectory toward sustainable growth and profitability.

We have delivered complete, proprietary AV technology — an integration of software and hardware — to enable earlier successes for our clients in constrained Level 4 autonomy. By choosing the middle mile – with defined point‑to‑point delivery – we have simplified some of the more complex AV challenges, enabling us to achieve full autonomy ahead of competitors. Given extensive knowledge of Gatik’s well‑defined, fixed route ODDs and hybrid architecture, we are able to hyper‑optimize our models with…