Tech Stack

Description

You will design massive multimodal Teacher models and distill them into efficient Student models that can search petabytes of sensor data in near real-time. You'll also build RL-based systems to optimize data discovery workflows and deploy models into production.

Requirements

• BS in Computer Science, Machine Learning, or related field or equivalent experience.
• 6+ years hands-on experience in ML engineering with focus on model optimization and deployment.
• Strong experience with model distillation or teacher-student training.
• Proven experience with reinforcement learning in production or research.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).

Responsibilities

• Architect and train teacher-student model frameworks for multimodal sensor data.
• Build RL-based policy learning and reasoning systems for autonomous driving.
• Deploy distilled and RL models into production, optimizing for latency and throughput.
• Prototype agentic workflows for autonomous reasoning and goal-directed behavior.
• Mentor junior engineers in model training, evaluation, and deployment.