ML Validation Engineer - Early Career
Core
Developing AI tools and research prototypes to verify and validate ML components for robotics and autonomous driving systems via simulation and performance monitoring.
Role type
Early-career applied ML research engineer (validation)
Builds
Simulation-based evaluation tools, performance monitoring systems, and issue observability solutions for autonomous vehicle stacks
Domain
Autonomous driving, robotics, machine learning validation
Deliverable
production ML models
Required skills
Python, PyTorch/JAX/TensorFlow, ML research prototyping, CI/CD pipeline integration, uncertainty modeling, scenario generation, deep learning evaluation
Preferred skills
Published research, patents, cross-functional collaboration
Technologies
Python, PyTorch, JAX, TensorFlow, CI/CD pipelines, diffusion models, generative models
Responsibilities
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 closed loop simulation validation; 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
