Principal Engineer Team Lead, Behavior Safety & Metrics

Jobgether; United States; Sur place; USD 240 000 - 330 000; Plein temps

Avantages offerts par ce poste

Medical insurance

Dental insurance

Vision insurance

401(k) matching

Health Savings Account

Life insurance

Pet insurance

Equity

Bonuses possible

Résumé du poste

Jobgether in the United States seeks a senior evaluation scientist to shape how autonomous driving systems are evaluated across prediction and planning. You will define evaluation strategies, develop quantitative frameworks, and connect model performance to real-world vehicle behavior.

Working with Safety, Infrastructure, Operations, Legal, and engineering teams, you will guide data-driven improvements throughout the lifecycle.

Qualifications

• Bachelor's degree in a technical field with 7+ years of experience, or advanced degree with 5+ years.
• Strong foundation in probability, statistics, and data science.
• Experience defining performance targets for safety and comfort.
• Proven ability to solve complex, cross-disciplinary engineering problems.

Responsabilités

• Serve as the technical authority for evaluation across Behavior teams and connect model development with system performance.
• Define and lead evaluation strategies for prediction and planning models, including open-loop and simulation-based assessments.
• Design and implement advanced performance metrics to measure impact on end-to-end system behavior.
• Incorporate counterfactual reasoning and reaction-time analysis into evaluation frameworks.
• Develop data mining strategies and assess dataset coverage across prediction and planning.
• Build scalable evaluation tools, pipelines, and processes with ML engineers and roboticists.
• Establish performance targets and acceptance criteria across safety, comfort, and driving assertiveness.
• Collaborate with Safety, Infrastructure, Operations, Legal, and other teams to guide design improvements.
• Ensure system changes deliver measurable improvements and meet launch criteria for safe autonomous driving.

Connaissances

Python

SQL

Data analysis

Statistics

Machine learning

Cross-functional collaboration

Communication

Hazard analysis methods

Formation

Bachelor's degree in Computer Science or related field

Master's or PhD with relevant experience

Outils

Waymo Open Dataset

nuScenes

Description du poste

Take a leading technical role in shaping how autonomous driving systems are evaluated, measured, and improved across prediction and planning. You will establish the evaluation strategy and quantitative frameworks that connect individual model performance with real-world vehicle behavior, helping ensure autonomous vehicles operate safely, comfortably, and confidently. Working at the intersection of machine learning, robotics, data science, and systems engineering, you will develop advanced metrics, scalable evaluation tools, and data mining strategies. You will also investigate system limitations, assess dataset coverage, and guide improvements throughout the model development lifecycle. Partnering with Safety, Infrastructure, Operations, Legal, and engineering teams, you will help define the evidence and performance standards needed to advance next-generation autonomous driving capabilities.

Accountabilities

• Serve as the technical authority for evaluation across Behavior teams, connecting model-level development with overall autonomous driving system performance.
• Define and lead evaluation strategies for prediction and planning models, including open-loop and simulation-based assessments.
• Design and implement advanced performance metrics, including machine learning-based approaches to measure model impact on end-to-end system behavior.
• Incorporate counterfactual reasoning and reaction-time analysis into evaluation frameworks to better understand system decisions and outcomes.
• Develop data mining strategies and assess the coverage, quality, and representativeness of training and evaluation datasets across prediction and planning.
• Build scalable evaluation tools, pipelines, and processes, identifying gaps and collaborating with machine learning engineers and roboticists to address complex technical challenges.
• Establish performance targets and acceptance criteria across safety, comfort, and driving assertiveness, supported by rigorous analysis and evidence.
• Work closely with Safety, Infrastructure, Operations, Legal, and other Systems teams to guide design improvements and assess the impact of new capabilities.
• Ensure that system changes deliver measurable improvements and meet the required launch criteria for safe and effective autonomous driving.

Requirements

• Bachelor's degree in Computer Science, Systems Engineering, Robotics, or a related technical field, with at least 7 years of relevant experience; alternatively, a master's degree or PhD with at least 5 years of experience.
• Strong foundation in probability, statistics, data science, and scientific methods applied to complex multi-agent systems.
• Proficiency in Python, SQL, and production-level data analysis, including statistical analysis and visualization.
• Experience defining performance targets and acceptance criteria for safety, comfort, and assertiveness, and producing evidence to support technical decisions.
• Demonstrated ability to solve complex, cross-disciplinary engineering problems and develop innovative, maintainable solutions.
• Proven experience leading technical initiatives, aligning stakeholders, and driving projects through the development process.
• Working knowledge of hazard and safety analysis methods, such as STPA, HAZOP, FMEA, and hazard analysis and risk assessment.
• Strong communication skills, with the ability to explain complex technical concepts to engineering teams, cross-functional partners, and executive stakeholders.
• Preferred experience applying statistical and machine learning methods to quantify performance, detect regressions, and identify behavioral patterns at scale.
• Deep experience in autonomous robotics prediction and/or planning, including evaluation of machine learning-based systems in production environments.
• Familiarity with public autonomous vehicle datasets and benchmarks, such as Waymo Open Dataset and nuScenes, as well as industry metrics for trajectory forecasting and motion planning.
• Experience building or using large-scale data pipelines.
• Familiarity with SOTIF, ISO 26262, UL 4600, AVSC behavior competencies, and other relevant industry standards is an advantage.

Benefits

• Base salary: $240,000–$330,000 USD.
• Potential additional compensation through bonuses and/or company equity.
• Medical, dental, and vision insurance.
• 401(k) retirement plan with company match.
• Health Savings Accounts (HSA).
• Life insurance.
• Pet insurance.
• Additional employee benefits and support programs, depending on eligibility.