with 18 years of experience as an AWS Cloud Solutions Architect, has been instrumental in the IT industry, particularly in leading a multinational consultancy firm for 13 years. His expertise includes AWS Cloud, AI/ML, and Data Analytics, where he has implemented impactful strategies and leveraged automation to enhance decision-making processes. Recognized for his competence in formulating C-suite strategies, Adeel integrates AI/ML and Advanced Analytics to achieve significant business milestones. He\'s committed to advocating for Responsible AI and advancing sustainable technology. Aspiring to excel as a Generative AI Specialist, he aims to optimize the secure application of Generative AI to boost productivity, facilitate the transition to a GenAI-driven landscape, and increase AWS Cloud Adoption. As a dedicated father of two, Adeel is motivated by the prospect of building a brighter future through consistent innovation.

Core Skills

AI/ML Technologies: Proficiency in Python Libraries: Advanced skills in Apache Arrow, Pandas, NumPy, PyTorch, TensorFlow, and Apple MLX, facilitating sophisticated data analysis and machine learning solutions. AI Techniques and Architecture: Deep understanding and application of GCN, Gradient Boosting, REL, RNN, LSTM, Transformers, and other advanced AI/NLP techniques, showcasing a broad and profound technical skillset. Image and Audio Processing: n leveraging OpenCV, ImageNet, facerecognize, CodeFomer, faceswap, REAL-ESRGA, deepfake, torchaudio, tortoise-tts, coqui-ai/TTS, whisper, Distilt whisper for cutting-edge visual and audio projects. Proficient in acoustic beamforming for noise source localization, emphasizing a multi-disciplinary approach to AI solutions. Machine Learning Platforms: Familiarity with keras, pytorch, CoreML, Onnxruntime platforms, demonstrating versatility in selecting the right tools for project requirements. Generative AI: Model Architecture Mastery: olid grasp of both foundational and innovative model architectures including Bert, T5, transformer, CNN, DistillBERT, RoBERTa, ELECTRA, FLAN-T5, highlighting adaptability and foresight in AI developments. Autoregressive LLM Development: Pioneered in building applications with a focus on prompt engineering, model fine-tuning, and response style customization, underlining creative problem-solving capabilities. Extensive expertise in developing large language model applications using both low-level APIs and high-level bindings in Python and Rust. Skilled in fine-tuning multi-model LLMs (LLaVa) using advanced techniques like DPO, LoRA, and Quantized LoRA. Hands-on experience with transformer models including gpt-neox, gpt2, custom GPT LLM architecture, utilizing platforms like facebookresearch/xformers for diverse AI applications. LLM Experimental Model Development: Expertise in building LLM-based applications, prompt engineering, and tuning. Hands-on experience with transformers models like gpt-neox, gpt2, and architectures with facebookresearch/xformers. Skilled in using simpletransformers for classification and other ML workflows. LLM Optimization: Extensive experience with Speculative Decoding, Quantization, Prompt Tuning, enabling LLMs to operate on consumer hardware. Research and Development: Conducted fine-tuning of multi-model LLMs (LLaVa), utilizing techniques like DPO, LoRA, and demonstrating leadership in AI research. Distributed Training and Inference: Knowledgeable in sparse training and inference techniques for GPT based models, highlighting efficiency in resource utilization. Vector Space and Databases: Deep understanding of embeddings, vector space, and vector databases including faiss, qdrant, pgvector/rds, enhancing capabilities in NLP and image processing. Gen AI based Autonomous Agents Application: Developed with langchain, AutoGen (Build many apps including simulating AWS Professional Team.