Muhammad E.

AI & Machine Learning Engineer specializing in deep learning, custom model training, LLM integration, data engineering, and AI-powered automation. I help businesses and research teams design, develop, train, evaluate, and deploy machine learning solutions. My work covers everything from data preprocessing and experimental pipelines to model development, performance evaluation, and production integration. Whether you need a custom deep learning training pipeline, an AI research prototype, an LLM-powered application, or a scalable data processing system, I can help turn complex technical requirements into reliable, reproducible solutions. What I Can Do for You Machine Learning & Deep Learning Develop and evaluate machine learning and deep learning models using Python, PyTorch, TensorFlow, and Scikit-learn. I work with model training, fine-tuning, custom training objectives, loss functions, optimization, evaluation, and performance analysis. Custom Training Pipelines & AI Research Build reproducible machine learning experiments, implement custom training loops, compare baseline approaches, and evaluate training strategies through ablation studies and controlled experiments. My focus is not just achieving high accuracy but understanding model behavior, validating experimental results, and developing reliable training methodologies. Time-Series Analysis & Predictive Modeling Work with sequential and time-dependent data, including preprocessing, feature engineering, pattern recognition, anomaly detection, and predictive modeling. LLMs & Generative AI Develop AI-powered applications using OpenAI, Gemini, Anthropic, and open-source models such as Qwen. Experience includes LLM fine-tuning, LoRA/PEFT, NLP, structured outputs, intelligent automation, and API integration. Data Engineering & Automated Pipelines Design scalable ETL/ELT pipelines for data ingestion, cleaning, transformation, validation, and storage. Build automated workflows using Python, cloud services, APIs, and databases. Model Evaluation & Reproducibility Implement structured evaluation workflows, baseline comparisons, ablation experiments, data leakage prevention, reproducible training configurations, and clear technical documentation. AI Applications & Backend Development Build AI-powered applications, REST APIs, backend services, and automation systems using Python, FastAPI, Docker, AWS, and Google Cloud. Technical Skills Programming: Python, SQL ML & Deep Learning: PyTorch, TensorFlow, Scikit-learn, XGBoost Model Training: Fine-tuning, LoRA/PEFT, Custom Training Loops, Loss Functions, Hyperparameter Optimization Research & Evaluation: Baseline Comparisons, Ablation Studies, Model Validation, Reproducibility LLMs: OpenAI, Gemini, Claude, Qwen, Hugging Face Data Engineering: ETL/ELT, Pandas, NumPy, Data Processing, Automation Cloud & Deployment: AWS, Google Cloud, Docker, FastAPI, REST APIs Why Work With Me? Strong foundation in AI, machine learning, and Python development Experience with deep learning models and experimental workflows Focus on reproducibility, evaluation, and reliable results Clean, maintainable, well-documented code Experience delivering AI and data engineering solutions for international clients Clear communication and a practical, problem-solving approach Let's Work Together Whether you're developing a new machine learning methodology, building a custom training pipeline, conducting AI experiments, or integrating AI into your business, I'd be happy to discuss your requirements and help build a reliable solution.