Location: Chennai
Experience: 4+ yrs

Responsibilities:

• Contribute to the design, training, and deployment of novel AI models for telematics applications
• Develop algorithms that model physical phenomena associated with vehicle and human movement
• Explore and implement advanced self-supervised learning methods tailored to multi-modal telematics sensor data
• Fine-tune upstream pretrained models or leverage their embeddings to solve downstream telematics tasks such as crash detection, driver risk scoring, and claims processing
• Build models robust to noise, missing data, and diverse real-world operating conditions
• Collaborate with engineers and product teams to integrate AI models into production systems
• Develop scalable training and inference pipelines using frameworks such as Ray, PyTorch DDP, or Horovod
• Optimize models for efficient deployment across cloud and edge/mobile environments
• Stay current with AI/ML research, applying new techniques to real-world telematics challenges
• Document and present findings, contributing to CMT’s AI/ML knowledge base
• Support junior team members through code reviews, collaboration, and knowledge sharing
• Complete any additional tasks as they arise

Qualifications:

• Bachelor’s degree or equivalent years of experience and/or certification in Artificial Intelligence, Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or a related field
• 4+ years of relevant experience in AI/ML (post-degree)
• Strong hands-on experience developing and training deep learning models, preferably transformers for time-series or multimodal data
• Familiarity with self-supervised learning and representation learning on noisy sensor data
• Proficiency in Python and data science libraries (e.g., Pandas, NumPy, scikit-learn)
• Strong experience with PyTorch (preferred) or TensorFlow for deep learning
• Practical experience with distributed training methods and efficient model training
• Experience with data processing pipelines and ML infrastructure (e.g., Spark, Airflow, Docker, AWS/GCP/Azure)
• Excellent problem-solving skills and ability to translate complex business problems into AI solutions
• Strong communication skills to effectively present technical concepts to diverse audiences
• Product-focused mindset with a track record of delivering impactful ML solutions

Nice to Haves:

• Master’s or PhD preferred
• Experience with model interpretability and explainability techniques (XAI)
• Familiarity with ethical AI principles, bias detection, and mitigation strategies
• Exposure to MLOps practices for managing the ML lifecycle
• Publications or open-source contributions in AI/ML