Systems Engineer - Behavior Verification

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Systems Engineer – Behavior Verification based in the United States.

Join an innovative technology environment at the forefront of Physical AI and autonomous transportation, where advanced engineering is helping shape the future of self-driving trucks and robotaxis. As a Systems Engineer specializing in Behavior Verification, you will play a critical role in ensuring autonomous driving software meets rigorous safety and performance standards before release. You will design scenario-based test strategies, establish verification criteria, and validate the evidence used to assess real-world driving behavior. Working closely with teams across simulation, motion planning, safety, evaluation, and platform engineering, you will identify behavioral deficiencies and strengthen the reliability of autonomous systems. Your work will directly influence software release decisions, ensuring that new capabilities are supported by robust, measurable evidence. This opportunity is ideal for a rigorous, analytical engineer who thrives in complex technical environments and is passionate about advancing safe, dependable autonomous mobility.

• Design comprehensive verification strategies: Develop, structure, and document scenario-based test sets that evaluate autonomous driving behavior, from minimum release requirements to comprehensive performance assessments.
• Govern software release readiness: Define and execute scenario validity checks, assess test set quality, and approve or reject test sets before they are used to evaluate software releases.
• Maintain test artifact quality: Establish continuous quality feedback processes for scenarios, taggers, graders, and the taxonomies supporting behavior verification, ensuring test artifacts remain accurate, consistent, and trustworthy.
• Translate requirements into measurable criteria: Collaborate with Behavior Requirements teams to convert behavioral expectations into clear, testable acceptance criteria and performance targets that support formal verification decisions.
• Investigate behavioral deficiencies: Analyze identified failures, find additional instances, quantify exposure to relevant scenarios, and feed missed issues back into the verification pipeline as test escapes.
• Distinguish software failures from simulation limitations: Determine whether observed issues represent genuine autonomous driving deficiencies or simulation artifacts, and communicate simulation fidelity gaps to the appropriate engineering teams.
• Coordinate cross-functional verification activities: Work with motion planning, simulation, evaluation, operations, safety methodology, and platform teams to align interfaces, responsibilities, and verification processes.
• Define verification phases and testing cadence: Establish appropriate testing frequencies and verification requirements for daily software releases, significant increases in operational exposure, and other critical development milestones.
• Support evidence-based release decisions: Deliver clear assessments of autonomous driving behavior, test coverage, and identified risks to inform decisions about software readiness and release progression.
• Continuously improve verification processes: Identify gaps in scenario coverage, refine test strategies, and help build scalable verification methodologies as the technology and organization evolve.

Requirements

• Bachelor's or master's degree in a relevant engineering or technical discipline, such as Software Engineering, Electrical Engineering, Computer Science, Robotics, Advanced Controls, Aerospace Engineering, or a related field.
• Professional experience verifying safety-critical systems, ideally within autonomous vehicles or other complex, safety-sensitive engineering environments.
• Demonstrated experience designing test cases from system requirements and evaluating test coverage, including identifying gaps and limitations in existing test sets.
• Applied statistical knowledge, including sample size selection, confidence assessment, and the ability to interpret what test results do and do not establish.
• Proficiency in Python and the ability to navigate, understand, and contribute to a large and complex codebase.
• Familiarity with autonomous vehicle requirements, driving behaviors, and systems engineering or design methodologies.
• Strong organizational skills, with the ability to structure, document, prioritize, and maintain large collections of test sets and verification strategies.
• Excellent analytical and problem-solving abilities, including a rigorous approach to evaluating evidence, identifying behavioral failures, and distinguishing genuine issues from simulation artifacts.
• Strong communication and cross-functional collaboration skills, including the ability to work diplomatically with teams that may have differing priorities or technical perspectives.
• A high degree of ownership, accountability, and commitment to quality, with the confidence to make evidence-based decisions and uphold verification standards.
• Adaptability, initiative, and a willingness to develop new processes in a growing technical organization.

Preferred qualifications:

• Experience with trucking, heavy vehicles, commercial transportation, or autonomous vehicle applications.
• Knowledge of machine learning systems, particularly model evaluation and the trade-offs between false positives and false negatives.
• Familiarity with relevant safety and regulatory frameworks, including NHTSA guidance, ISO 26262, and Safety of the Intended Functionality (SOTIF).
• Experience using tools and methodologies to extract scenario coverage and exposure metrics from large-scale driving log datasets.
• Comfort working within a newly established team where verification processes, standards, and workflows must be developed and continuously improved.

Benefits

• Competitive annual salary: USD $149,000–$190,000, depending on qualifications, experience, and other relevant compensation factors.
• Additional compensation: Eligibility for discretionary equity incentive awards and an annual performance bonus.
• Comprehensive healthcare coverage: Medical, dental, and vision benefits for eligible full-time employees.
• Flexible paid time off: Unlimited vacation policy, subject to applicable company guidelines and responsibilities.
• Flexible working arrangements: Flexible working hours and work-from-home support.
• Team-building opportunities: Regularly scheduled team activities and social events, both in person and virtually.
• Office amenities: Daily drinks, snacks, and catered meals when working from the office.
• Professional development: Opportunities to expand expertise in Physical AI, autonomous driving, behavioral verification, simulation, and safety engineering.
• Meaningful technical impact: Contribute directly to the development and verification of autonomous transportation technologies designed to improve safety and transform mobility.
• Collaborative environment: Work alongside talented engineers and specialists in AI, robotics, software, and autonomous systems.
• Inclusive workplace: Commitment to equal opportunity, accessibility, diversity, and a supportive environment where people from all backgrounds can contribute and grow.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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