Description :
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 VLMsProficiency in TensorFlow, PyTorch, or equivalent deep learning frameworksStrong knowledge of GPU / NPU acceleration and Edge-AI deploymentExperience with model optimization, distillation, and quantization techniquesProven track record of AI integration into large-scale production systemsFamiliarity with cloud platforms (AWS, Azure, GCP) and MLOps workflows(ref : hirist.tech)