AI Research Scientist - Safety

What you'll do

• Develop world models, simulation frameworks, and physical reasoning methods to evaluate complex driving edge cases.
• Implement safety validation, out-of-distribution detection, failure analysis, and uncertainty estimation for robust system integration.
• Transfer research into operational platforms, advise senior leadership, and publish and present research.

What they ask for

• Ph.D. in Computer Science, Machine Learning, Robotics, Artificial Intelligence, or a related quantitative field.
• 3+ years of dedicated research experience in world models, generative dynamics, self-supervised learning, or physical reasoning for autonomous systems.
• 2+ years of industrial R&D experience creating, fine-tuning, and deploying large-scale machine learning models and safety-critical algorithms.
• Proficiency in Python and deep learning frameworks (PyTorch or JAX).

Nice to have

• Expertise in AI safety techniques, including alignment, adversarial robustness, interpretability (XAI), failure mode analysis, and uncertainty quantification.
• Experience with C++, high-performance distributed training pipelines, top-tier publications, or patent contributions.

Pay

$165,000 - $185,000 USD base salary

Tools

Python, PyTorch, JAX, C++

AI focus

AI safety, alignment, model reliability, generative world models, simulation, physical reasoning, safety validation, OOD detection, failure analysis, and uncertainty estimation for ADAS and autonomous systems.