Autonomous Driving Verification Engineer - Remote

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

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.