Tech Stack

Description

In this role, you will design and train teacher-student models for multimodal sensor data, build reinforcement learning systems for data discovery, and deploy optimized models into production. Your work will directly accelerate the model improvement lifecycle by enabling efficient mining of petabytes of autonomous driving data.

Requirements

• BS in CS, ML, or related field; 6+ years ML engineering experience
• 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)
• Experience deploying ML models in cloud environments and optimizing for inference

Responsibilities

• Architect and train teacher-student model frameworks for multimodal sensor data
• Build RL-based policy learning and reasoning systems for autonomous driving
• Optimize model deployment for real-time inference on GPU/CPU clusters
• Research and integrate agentic workflows for autonomous reasoning
• Drive production reliability with fault tolerance and cost optimization