Systems Engineer - Behavior Verification

Jobgether; United States; Remote; USD 115,000 - 146,000; Full time

Benefits offered by this job

Competitive compensation

Flexible work arrangements

Health benefits

Professional growth opportunities

Job summary

Jobgether seeks an experienced verification engineer to design and manage scenario-based testing for autonomous driving systems. You will coordinate cross-functional teams to ensure test coverage and release readiness, translating complex requirements into measurable verification criteria.

You will analyze failures, differentiate real defects from simulation limitations, and contribute to scalable verification methodologies in a dynamic organization.

Qualifications

• Proficiency in Python and statistical methods.
• Ability to design test cases from system requirements.
• Strong analytical and problem-solving abilities.
• Experience documenting verification strategies and test sets.

Responsibilities

• Design comprehensive verification strategies for autonomous driving behavior across release stages.
• Govern software release readiness by reviewing test sets and validation quality.
• Maintain data quality for scenarios, taggers, graders, and taxonomies.
• Translate requirements into measurable, verifiable criteria and standards.
• Investigate failures, identify missed issues, and feed back into the verification pipeline.
• Distinguish genuine defects from simulation artifacts and communicate fidelity gaps.

Skills

Python

Statistics

Analytical thinking

Cross-functional collaboration

Communication skills

Ownership

Adaptability

Education

Bachelor’s or Master’s degree in a relevant engineering or technical discipline

Job description

Accountabilities

• Design comprehensive verification strategies: Develop, structure, and document scenario-based test sets that assess autonomous driving behavior, ranging from minimum release requirements to comprehensive performance evaluations.


• Govern software release readiness: Define and execute scenario validity checks, review test set quality, and approve or reject test sets before they are used to evaluate software releases.


• Maintain test data quality: Establish continuous quality feedback processes for scenarios, taggers, graders, and the taxonomies supporting behavior verification, ensuring that 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, performance targets, and formally agreed verification standards.


• Investigate behavioral deficiencies: Analyze identified failures, search for additional instances, quantify the system's 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 behavioral issues represent genuine system deficiencies or simulation artifacts, and communicate simulation fidelity gaps to the appropriate engineering teams.


• Coordinate cross-functional verification activities: Work closely with motion planning, simulation, evaluation, operations, safety methodology, and platform teams to align interfaces, responsibilities, and verification processes.


• Define verification phases and cadence: Establish appropriate testing frequencies and verification requirements for daily software releases, significant exposure increases, and other critical development milestones.


• Strengthen release decision-making: Provide clear, evidence-based assessments of autonomous driving performance to support decisions about software readiness, risk, and release progression.


• Improve verification processes: Identify gaps in test coverage, refine test strategies, and contribute to the development of scalable verification methodologies as the team and technology 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, advanced driver‑assistance systems, robotics, or other complex 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 interpretation of test results and their limitations.


• 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 and the ability to structure, document, prioritize, and maintain large collections of test sets and verification strategies.


• Excellent analytical and problem-solving abilities, with a rigorous approach to evaluating evidence, identifying failures, and distinguishing genuine behavioral issues from testing or simulation artifacts.


• Strong cross-functional collaboration and communication 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 and a proactive mindset, with the ability to establish processes, resolve ambiguity, and contribute effectively in a developing technical organization.

Preferred qualifications:

• Experience with trucking, heavy vehicles, commercial transportation, or other large-scale 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 refined.

Benefits

• Competitive annual salary: CAD $160,000–$204,000 for the Canadian location, 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.


• Collaborative work environment: Opportunities to work alongside experienced engineers and specialists in autonomous driving, AI, robotics, and safety-critical systems.


• Team-building and social activities: Regularly scheduled events and activities held in person, off-site, and virtually.


• Office amenities: Daily drinks, snacks, and catered meals when working from the office.


• Meaningful technical impact: Contribute directly to the development and verification of autonomous transportation technologies designed to improve safety and transform mobility.


• Professional growth: Opportunities to develop expertise in Physical AI, behavioral verification, simulation, safety engineering, and next-generation autonomous systems.


• Inclusive workplace: Commitment to diversity, accessibility, equal opportunity, and a supportive environment where people from all backgrounds can contribute and grow.