Tech Stack

Description

You will help design and develop next-generation AI models for telematics applications, working at the intersection of cutting-edge AI research and real-world data to improve road safety. Your work will involve training novel foundation models, fine-tuning them for tasks like crash detection and risk assessment, and deploying them into production.

Requirements

• Bachelor's in AI, CS, EE, Physics, Math, Statistics or related field
• 4+ years experience in AI/ML post-degree
• Strong hands-on experience with deep learning, especially transformers for time-series or multimodal data
• Proficiency in Python, PyTorch (preferred), and data science libraries
• Experience with distributed training and ML infrastructure (Spark, Airflow, Docker, cloud)

Responsibilities

• Design and train novel AI models for telematics applications
• Develop self-supervised learning methods for multi-modal sensor data
• Fine-tune pretrained models for crash detection, risk scoring, and claims processing
• Build scalable training and inference pipelines with Ray, PyTorch DDP, or Horovod
• Optimize models for cloud and edge/mobile deployment