Available to hire
Hi, I’m Ahmad Hayes, a Senior Machine Learning Engineer with over a decade of experience in building and deploying scalable AI solutions. I specialize in Generative AI, Large Language Models, and Natural Language Processing, and I love working with transformer-based architectures and vector databases to solve real-world problems.
I’m passionate about creating production-ready AI applications that make a difference. I’ve worked extensively with cloud platforms like AWS, GCP, and Azure, and I enjoy mentoring junior engineers and collaborating on cross-functional AI projects. When I’m not engineering models, I’m exploring new advances in prompt engineering and MLOps to keep pushing the boundaries of what’s possible.
Work Experience
Senior Machine Learning Engineer at Klarity Labs
January 1, 2021 - PresentDesigned and deployed end-to-end Generative AI systems using transformer-based LLMs (BERT, RoBERTa, GPT, T5) for enterprise NLP use cases including conversational AI, summarization, and semantic search. Built and scaled Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases such as FAISS and Pinecone, optimized for real-time contextual search and knowledge retrieval. Led architecture and development of intelligent document understanding systems leveraging entity extraction, OCR pipelines, and attention-based models. Developed production-grade ML APIs using FastAPI and containerized services using Docker and Kubernetes for scalable deployment. Created automated pipelines for prompt engineering, model evaluation, and multi-run experiment tracking using MLflow and Weights & Biases. Applied techniques like LoRA, PEFT, and parameter-efficient fine-tuning for optimizing large transformer models on limited compute. Integrated LangChain for building modular LLM-powered
Senior Machine Learning Engineer at CognitiveScale
December 31, 2020 - July 25, 2025Led the design and development of multilingual NLP systems for sentiment analysis, text classification, and information extraction using modern deep learning models. Integrated pre-trained models like BERT and XLNet into customer-facing applications, improving semantic understanding and multilingual capabilities. Engineered pipelines for time-series forecasting and anomaly detection to predict operational KPIs, using statistical models and recurrent neural networks. Developed custom transfer learning workflows to reduce training data requirements and boost generalization across domains. Deployed models via REST APIs using Flask and TensorFlow Serving, enabling real-time predictions for downstream applications. Created automated ETL workflows and model orchestration pipelines using Apache Airflow and Docker for reproducibility and scalability. Designed modular ML pipelines with feature extraction, training, hyperparameter tuning, and automated retraining based on drift detection. Partne
Machine Learning Engineer at Mavericks United
June 30, 2019 - July 25, 2025Led the design and development of multilingual NLP systems for sentiment analysis, text classification, and information extraction using modern deep learning models. Integrated pre-trained models like BERT and XLNet into customer-facing applications, improving semantic understanding and multilingual capabilities. Engineered pipelines for time-series forecasting and anomaly detection to predict operational KPIs, using statistical models and recurrent neural networks. Developed custom transfer learning workflows to reduce training data requirements and boost generalization across domains. Deployed models via REST APIs using Flask and TensorFlow Serving, enabling real-time predictions for downstream applications. Created automated ETL workflows and model orchestration pipelines using Apache Airflow and Docker for reproducibility and scalability. Designed modular ML pipelines with feature extraction, training, hyperparameter tuning, and automated retraining based on drift detection. Partne
Senior Machine Learning Engineer at Klarity Labs
January 1, 2021 - PresentDesigned and deployed end-to-end Generative AI systems using transformer-based LLMs for enterprise NLP use cases including conversational AI, summarization, and semantic search. Built and scaled Retrieval-Augmented Generation pipelines integrated with vector databases such as FAISS and Pinecone, optimized for real-time contextual search and knowledge retrieval. Led architecture and development of intelligent document understanding systems leveraging entity extraction, OCR, and attention-based models. Developed production-grade ML APIs using FastAPI with Docker and Kubernetes for scalable deployment. Created automated pipelines for prompt engineering and experiment tracking using MLflow and Weights & Biases. Applied techniques like LoRA and PEFT for optimizing large transformer models. Integrated LangChain for building modular LLM-powered applications. Built internal frameworks for A/B testing and latency benchmarking of GenAI services. Mentored junior engineers and led technical design
Senior Machine Learning Engineer at CognitiveScale
December 31, 2020 - July 25, 2025Led the design and development of multilingual NLP systems for sentiment analysis, text classification, and information extraction using modern deep learning models. Integrated pre-trained models like BERT and XLNet into customer-facing applications improving semantic understanding and multilingual capabilities. Engineered pipelines for time-series forecasting and anomaly detection to predict operational KPIs using statistical models and recurrent neural networks. Developed custom transfer learning workflows to reduce training data requirements and improve domain generalization. Deployed models via REST APIs using Flask and TensorFlow Serving for real-time predictions. Created automated ETL workflows and model orchestration pipelines with Apache Airflow and Docker. Designed modular ML pipelines including feature extraction, training, tuning, and retraining based on drift detection. Partnered with teams to define ML problem statements and success metrics. Implemented data labeling and a
Machine Learning Engineer at Mavericks United
June 30, 2019 - July 25, 2025Led design and development of multilingual NLP systems for sentiment analysis, text classification, and information extraction with modern deep learning models. Integrated pre-trained models like BERT and XLNet into applications for improved semantic understanding and multilingual support. Engineered pipelines for time-series forecasting and anomaly detection using statistical models and recurrent neural networks to predict operational KPIs. Developed custom transfer learning workflows reducing training data needs and enhancing domain generalization. Deployed models via REST APIs using Flask and TensorFlow Serving for real-time application. Created automated ETL workflows and orchestration pipelines using Apache Airflow and Docker. Designed modular ML pipelines with feature extraction, training, hyperparameter tuning, and automated retraining based on drift detection. Collaborated with product and engineering teams on ML problem definitions, metrics, and iterative experiments. Implemen
Education
Master of Science at Preston University
January 11, 2030 - July 25, 2025Master of Science at Preston University
January 1, 2010 - December 31, 2012Qualifications
Industry Experience
Software & Internet, Professional Services, Financial Services, Healthcare, Media & Entertainment
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