AI Engineer (HS_Kitchen)

Design, develop, optimize, and deploy Machine Learning and Deep Learning models specifically for resource-constrained edge computing devices.

Develop and maintain end-to-end ML pipelines involving preprocessing, training, validation, and deployment targeting low-resource platforms with focus on performance, accuracy, and power efficiency.

Evaluate, benchmark, and continuously improve AI models for latency, memory use, computational efficiency, accuracy, robustness, and scalability in embedded and edge systems.

Experience: 2-5 years in AI/ML, Deep Learning, or related field involving edge computing model development.

Technical skills: Strong understanding and hands-on experience in Machine Learning, Deep Learning, model optimization, transfer learning, and statistical modeling.

Proficiency with AI/ML frameworks: TensorFlow, PyTorch, Keras, Scikit-Learn.

Programming skills: Strong Python and good C++ programming abilities.

Experienced in developing and deploying AI/ML models optimized for edge and embedded systems with resource constraints.

Skilled at model optimization techniques such as quantization, pruning, and transfer learning to ensure power efficiency and performance.

Able to operate in cross-functional teams integrating AI models into hardware platforms and continuously benchmarking model efficiency and accuracy.