ML Validation Research Engineer - Early Career

Job Description

• Prototype research concepts into performant tools integrated into CI/CD and large-scale validation pipelines.
• Develop AI-tools to improve performance monitoring and observability for autonomous vehicle stack
• Advance ML research for open and and closed loop simulation validation.
• Develop AI-centric automations to make issue triage and root cause analysis more scalable
• Develop scenario generation, coverage-guided testing, and rare-event discovery tooling.
• Create robust metrics, predictors, uncertainty and Out-of-Distribution detection methods for autonomy ML systems.
• Evaluate deep learning modules across perception, prediction, and planning in realistic sensor and traffic simulation.
• Improve behavioral coverage and hazard-aligned metrics used in release readiness decision making.
• Collaborate with Simulation, Safety, Systems Engineering, and cross-functional partners.
Author technical documentation, white papers, and contribute to validation methodology standards.

• Scenario synthesis (diffusion models, generative models, counterfactuals)
• Coverage-based and fuzzing-based evaluation for autonomy behavior
• Uncertainty estimation, calibration, conformal prediction, OOD detection
• Robustness testing and perturbation frameworks
Test suite prioritization, failure mining, and regression analysis

• B.Sc or MS in ML, Robotics, Computer Science, or work related experience
• Strong proficiency in Python, PyTorch/JAX/TensorFlow
• Demonstrated ability to translate complex ML research ideas into functional prototypes
• Experience integrating ML evaluation into CI/CD pipelines
• Proven research impact through published work, internal tools, or patents
• Strong communication skills and ability to collaborate cross-functionally

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