Opening For AI/ML Engineer

Key Responsibilities

• Design, Build and deploy solutions using modern AI/ML techniques, including supervised, unsupervised, deep learning, self-supervised, and representation learning approaches.
• Perform model optimization for deployment, including latency reduction, memory optimization, and hardware-aware tuning for embedded and edge AI environments.
• Process and analyze multi-sensor automotive data such as GPS, camera,radar and time-series signals for perception and decision-making tasks.
• Develop image processing algorithms for vision-based AI systems, involving development of models for detection, classification, segmentation and tracking.
• Conduct experimentation, benchmarking, error analysis, and iterative model improvements.
• Stay updated with latest research trends and translate them into scalable engineering solutions.

Preferred Qualifications & Experience

• Experience 2 to 5 Yrs
• Experience in automotive AI domains such as ADAS, autonomous systems, driver monitoring, or perception systems.
• Strong hands-on experience in image processing, computer vision, and deep learning-based vision models (e.g., CNNs, Transformers for vision, segmentation/detection architectures).
• Familiarity with real-time video analytics and multi-camera systems.
• Knowledge of AI model optimization techniques such as quantization, pruning, distillation, and graph optimization.
• Experience with edge AI platforms and deployment toolchains such as TensorRT, ONNX, OpenVINO, or equivalent.
• Familiarity with sensor fusion techniques and multi-modal learning approaches.

Experience working with Python and C++, and AI frameworks such as PyTorch or TensorFlow.