AI Research Resident collaborates on research projects developing benchmarks and environments for long-horizon AI agents, identifying model failure modes, and training autonomous agents. Requires current MS/PhD enrollment, RL experience, systems engineering, and strong publications.
Build state-of-the-art ML models to predict traffic behavior for autonomous driving, using generative sequence modeling and controllable agents for planning and simulation. Requires PhD preferred, 2+ years deploying ML systems, and expertise in PyTorch and robotics ML.
Develops and optimizes post-training algorithms for agent RL platforms, focusing on LLM training, inference frameworks, and multi-agent systems. Requires 1-3 years production LLM experience, expertise in PyTorch/CUDA, RLHF/PPO, and advanced degree.
Develops and deploys state-of-the-art ML models and agents for enterprise GenAI using RL training and post-training algorithms. Requires 1-3 years LLM production experience, RLHF expertise, recent top publications, and advanced CS degree.
Advances AI products through post-training SOTA LLMs using supervised and reinforcement learning techniques on rich query datasets. Owns data pipelines, training frameworks, and model integration while collaborating across teams. Requires 2-6+ years in large-scale LLMs and Python/PyTorch expertise; PhD preferred.
Develops state-of-the-art generative models like diffusion and flow-matching for autonomous planning in self-driving tech. Requires PhD or MSc with 2-3 years experience in generative modeling for robotics, strong Python/C++ skills, and top research publications.