Staff Systems Engineer – Safety Methodologies

Jobtailor; Arizona; On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor in Arizona seeks a senior professional to develop safety datasets spanning simulation and real-world testing to inform driverless release decisions.

You will validate evaluation pipelines, create structured safety artifacts, and mentor peers while collaborating across teams to enable evidence-backed readiness decisions.

Qualifications

• Undergrad required; Masters or PhD within an engineering discipline preferred.
• 7+ years of automotive, robotics or closely related industry experience.
• Experience with using simulation and real-world testing to make readiness decisions.
• Excellent scripting and data analysis skills (Python, SQL).
• Solid foundation in statistics.
• Experience with building a strong safety case for autonomous vehicles.
• Ability to communicate complex concepts or data in a simple-yet-accurate manner.
• Collaborative team player who works effectively across functional boundaries, driving evidence-backed decisions.
• Passionate about autonomy, solving hard problems, and creating innovative solutions.
• Experience in launching a driverless product.
• Experience implementing software systems components.
• Experience building software systems from scratchExperience in machine learning.
• Proficiency with data mining and advanced statistical analysis

Responsibilities

• Develop sample-efficient, high-signal safety datasets across simulation and closed-course track testing to inform driverless release testing
• Establish and manage a feedback loop from on-road monitoring and safety-relevant events to expand and refine test coverage
• Validate and optimize safety evaluation pipelines through comparative analyses of safety frameworks and benchmark criteria
• Create clear, structured safety artifacts traceable to validation evidence for transparent readiness decisions
• Mentor peers and foster technical excellence and cross-team collaboration

Skills

Python Programming

SQL Proficiency

Data Analysis

Machine Learning Experience

Statistics

Safety Case Development

Education

Bachelor’s degree in an engineering discipline

Master’s degree (preferred)

PhD (preferred)

Tools

Python

SQL

Data Mining

Simulation Testing

Benchmark Criteria Validation

Software System Implementation

Job description

Develop sample-efficient, high-signal safety datasets across simulation and closed-course track testing to inform driverless release testing
Establish and manage a feedback loop from on-road monitoring and safety-relevant events to expand and refine test coverage
Validate and optimize safety evaluation pipelines through comparative analyses of safety frameworks and benchmark criteria
Create clear, structured safety artifacts traceable to validation evidence for transparent readiness decisions
Mentor peers and foster technical excellence and cross-team collaboration

Requirements

• Undergrad required; Masters or PhD within an engineering discipline preferred
• 7+ years of automotive, robotics or closely related industry experience
• Experience with using simulation and real-world testing to make readiness decisions
• Excellent scripting and data analysis skills (Python, SQL)
• Solid foundation in statistics
• Experience with building a strong safety case for autonomous vehicles
• Ability to communicate complex concepts or data in a simple-yet-accurate manner
• Collaborative team player who works effectively across functional boundaries, driving evidence-backed decisions
• Passionate about autonomy, solving hard problems, and creating innovative solutions
• Experience in launching a driverless product
• Experience implementing software systems components
• Experience building software systems from scratchExperience in machine learning
• Proficiency with data mining and advanced statistical analysis

Core Competencies

Demonstrates expertise in developing safety datasets and validation pipelines for autonomous vehicles, leveraging simulation and real-world testing. Strong analytical skills in data analysis, statistics, and machine learning are essential for making evidence-backed readiness decisions.

Highest-signal resume keywords

• Python Programming
• SQL Proficiency
• Safety Case Development
• Machine Learning Experience
• Data Analysis Skills

Hard Skills

• Data Analysis
• Statistical Analysis
• Simulation Testing
• Safety Evaluation
• Software System Implementation
• Autonomous Vehicle Safety
• Scripting Skills
• Benchmark Criteria Validation
• Safety Artifact Creation
• Data Mining

Soft Skills

• Collaborative Team Player
• Effective Communication
• Mentoring Skills
• Problem Solving
• Cross-Team Collaboration

Industry Keywords

• Automotive Industry
• Robotics Industry
• Driverless Technology
• Safety Frameworks
• Readiness Decisions