AI/Data Resident

Role overview

The resident will work on research and engineering challenges in deep learning for autonomous driving, with a focus on advancing perception and control systems. The position combines hands-on modeling work with systems-level optimization, bridging cutting-edge research and real-world deployment.

Responsibilities

- Research and prototype deep learning architectures aimed at improving perception and control performance for autonomous driving - Design, train, and validate models on relevant driving datasets and in simulation environments - Optimize trained networks for latency, memory footprint, and robustness to meet deployment constraints - Integrate models into production or inference pipelines and monitor runtime behavior and stability - Run controlled experiments, benchmark alternative approaches, and document methodology, results, and engineering trade-offs

Requirements

- Practical experience building, training, and evaluating deep learning models in a framework such as PyTorch or TensorFlow - Working understanding of computer vision, sequence modeling, or reinforcement learning as applied to perception or control - Strong Python skills and familiarity with standard data and experiment management tooling - Ability to read recent research papers and translate ideas into clean, reproducible implementations - Comfort moving between research code and production-style codebases