Tech Stack

Description

You will lead the design, pre-training, fine-tuning, and deployment of novel foundation models for vehicle telematics, working on first-of-its-kind LLMs from petabyte-scale sensor data to enhance risk assessment, driver engagement, and crash processing.

Requirements

• Bachelor's degree in AI, CS, EE, Physics, Math, Statistics, or related field
• 7+ years professional experience in AI/ML
• 3+ years hands-on experience developing and deploying foundation models
• Expertise in time-series transformer architectures for sensor fusion
• Deep experience with self-supervised learning on noisy real-world sensor data

Responsibilities

• Lead design, pre-training, fine-tuning, and deployment of foundation models for vehicle telematics
• Develop algorithms for modeling automotive physics and human driving behavior
• Pioneer self-supervised learning techniques for multi-modal telematics sensor data
• Build scalable training and inference pipelines using Ray, PyTorch DDP, or similar
• Integrate AIs into production systems and optimize for cloud/edge deployment