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-driven methods, risk assessment, and collaboration with cross-functional teams to ensure system safety and performance.
Key Responsibilities
- Develop and execute reliability strategies for components and systems
- Perform FMEA, FMEDA, Weibull, and fault tree analyses
- Define reliability metrics 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 relevant standards
- Analyze validation and fleet data to detect trends, failure precursors, and degradation
- Collaborate on predictive maintenance tools, dashboards, and fault detection models
- Work with cross-functional teams to integrate reliability into all development stages
- Support incident investigations, certification, and continuous improvement processes
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 programming languages 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
- 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
- Experience developing models to evaluate risk across system behaviors and scenarios
- Ability to support safety case development and ensure compliance with ISO 26262, ISO 21448, UL4600
- Experience analyzing validation and fleet data to detect trends, failure precursors, and degradation
- Ability to collaborate on predictive maintenance tools, dashboards, and fault detection models
- Strong communication skills with excellent organizational and project management abilities
Benefits & Perks
Salary range: $160,000 - $240,000
Work schedule: Onsite 5 days a week
Work environment perks: Collaborative and inclusive culture emphasizing respect, agility, and diversity
Additional benefits: Opportunities for professional growth and contribution to innovative autonomous vehicle technology, involvement in safety and compliance projects, access to cutting-edge data analysis and reliability engineering tools
Ready to Apply?
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