AL Model Engineering Expertise : Deep proficiency in AI model engineering, that includes :

- Training and fine-tuning Vision Language Models (VLM), large language models (LLMs) and other Deep Learning (DL) architectures.

- Model optimization, quantization, and deployment for latency and throughput.

- Model evaluation and monitoring in production environments.

- Creating Small Language Models using Distillation, Pruning etc.

- Worked on accelerating AI training and inference, with GPU and NPU on Compute, Edge and Mobile platforms with SOCs from NVIDIA, Qualcomm etc.

- AI Solution Development : Build and integrate AI capabilities (e.g., computer vision, NLP, recommendation systems) into production-grade Web/Mobile App software.

- Scalability & Performance : Experience scaling AI systems for high-volume, real-time applications, leveraging Cloud-Native or Edge-AI technologies.

- Data-Driven Development : Strong understanding of data pipelines and feature engineering for AI applications.

Key Skills & Expertise :

- Deep expertise in AI model engineering, LLMs, and VLMs

- Proficiency in TensorFlow, PyTorch, or equivalent deep learning frameworks

- Strong knowledge of GPU/NPU acceleration and Edge-AI deployment

- Experience with model optimization, distillation, and quantization techniques

- Proven track record of AI integration into large-scale production systems

- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps workflows