Counterfactual Safety & Simulation Architect

Jobtailor

Sunnyvale (CA)

On-site

USD 190,000 - 240,000

Full time

4 days ago
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Job summary

Jobtailor in Sunnyvale, CA, is seeking a senior engineer to set the technical strategy and architecture for counterfactual behavior evaluation in autonomous vehicles. You will lead cross-functional efforts across Safety, Simulation, Human Factors, Legal, Product, and Operations to validate models against benchmarks and to deploy scalable pipelines for large-scale scenario analysis.

You have 10+ years in autonomous vehicles or related fields, with strong Python skills, leadership across teams,

Qualifications

  • Master’s degree in systems engineering, mechanical engineering, aerospace engineering, electrical engineering, computer science, robotics, human factors, or a related field
  • 10+ years of professional experience in autonomous vehicles, robotics, vehicle development, simulation, systems engineering, human factors, or safety-critical validation
  • Proven record of evaluating autonomous vehicles for a commercial fleet, launch, supervised release, or other high-consequence product decision
  • Strong understanding of human behavior modeling, driver response, perception and reaction time, vehicle dynamics, uncertainty, and the limits of model-based conclusions
  • Deep experience building or leading counterfactual, replay, crash reconstruction, incident analysis, or comparable simulation-based evaluation capabilities
  • Professional experience with simulation evaluation at scale, including scenario generation, parameter sweeps, distributed execution, reproducibility, data quality, and trade-offs between fidelity, confidence, runtime, and cost
  • Strong Python and agentic workflow experience
  • Comfort designing and reviewing production-quality analysis, simulation, and validation software and using code to investigate engineering questions
  • Strong written and verbal communication skills, with ability to explain technical results, assumptions, and limitations to engineering and non-engineering stakeholders
  • Demonstrated technical leadership across organizational boundaries and evidence of setting direction beyond a single project through a methodology, platform, framework, or reusable validation capability adopted by other teams

Responsibilities

  • Set the technical strategy and architecture for counterfactual behavior evaluation
  • Operationalize safety-defined attentive-human benchmarks, counterfactual simulation following human intervention, alternate-policy comparisons, and controlled scene perturbations
  • Convert real incidents and simulation events into executable, provenance-preserving scenarios
  • Implement and validate human and other road-user response models against benchmarks and requirements
  • Define and deploy scalable pipelines for parameter extraction, scene reconstruction, counterfactual swaps, fuzzing, simulation execution, outcome estimation, and analysis of large scenario sets
  • Establish validation methods for the counterfactual product and outputs, including baseline comparisons, replay and closed-course evidence, model limitations, confidence, traceability, and appropriate use of results
  • Lead work across Behavior, Simulation, Safety, Human Factors, Legal, Product, and Operations
  • Turn complex results into engineering actions, safety-case evidence, and release recommendations

Skills

Counterfactual Behavior Evaluation
Human Behavior Modeling
Simulation Evaluation at Scale
Python Programming

Education

Master’s degree in Systems Engineering or related field

Tools

Simulation Software
Analysis Tools
Validation Software

Job description

Jobtailor in Sunnyvale, CA, is seeking a senior engineer to set the technical strategy and architecture for counterfactual behavior evaluation in autonomous vehicles. You will lead cross-functional efforts across Safety, Simulation, Human Factors, Legal, Product, and Operations to validate models against benchmarks and to deploy scalable pipelines for large-scale scenario analysis.

You have 10+ years in autonomous vehicles or related fields, with strong Python skills, leadership across teams,

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