Job Description
The Reliability and Risk Engineer at Gatik is responsible for analyzing, predicting, and improving the safety and reliability of autonomous trucking systems through data analysis, risk assessment, and development of reliability strategies, working closely with cross-functional teams to ensure system safety and performance.
Key Responsibilities
- Develop and implement reliability strategies for vehicle components and systems
- Perform failure mode and effects analyses (FMEA, FMEDA), Weibull, and fault tree analyses
- Define and monitor reliability metrics such as MTBF, MTTR, and failure rates
- Conduct accelerated life testing and analyze design performance statistically
- Apply probabilistic risk assessment methods like Monte Carlo simulations and Bayesian inference
- Create models to evaluate system risk across various behaviors and scenarios
- Support safety case development and ensure compliance with relevant safety standards
- Analyze fleet and validation data to identify failure trends and degradation
- Collaborate on predictive maintenance tools, dashboards, and fault detection models
- Assist in incident investigations, certification processes, and continuous improvement initiatives
Requirements
- Master's or PhD in Mechanical Engineering, Electrical Engineering, Systems, Reliability, Statistics, Mathematics, or a related field
- At least 5 years of experience in reliability engineering or risk analysis in autonomous or safety-critical systems
- Strong skills in Python, R, MATLAB, or similar software for statistical modeling
- Familiarity with standards such as 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
- Excellent communication skills and strong organizational and project management abilities
- Ability to develop and execute reliability strategies for components and systems
- Experience performing FMEA, FMEDA, Weibull analysis, and fault tree analysis
- Ability to define reliability metrics such as MTBF, MTTR, and failure rates, and lead root cause investigations
- Experience conducting accelerated life testing and assessing design performance statistically
- Ability to apply probabilistic risk methods like Monte Carlo simulations and Bayesian inference
- Developing models to evaluate risk across system behaviors and scenarios
- Supporting safety case development and ensuring compliance with ISO 26262, ISO 21448, UL4600 standards
- Analyzing validation and fleet data to detect trends, failure precursors, and degradation
- Collaborating on predictive maintenance tools, dashboards, and fault detection models
- Working closely with cross-functional teams to integrate reliability into all development stages
- Supporting incident investigations, certification processes, and continuous improvement initiatives
Benefits & Perks
Salary range of 160,000-240,000 USD
Onsite work schedule, 5 days a week
Work environment perks related to a diverse and inclusive culture emphasizing collaboration, respect, and agility
Opportunities for professional growth and contribution to innovative autonomous vehicle technology
Ready to Apply?
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