Matthew A.

Senior AI/ML Engineer with 7+ years of experience building intelligent systems and deploying production-grade ML models. Proficient in Python, PyTorch, TensorFlow, and LLM integrations, with expertise in NLP, data engineering, model optimization, and MLOps. Proven ability to lead cross-functional teams and architect scalable ML pipelines across healthcare, video analytics, and enterprise platforms

Senior AI/ML Engineer at Adecco (2021-06 – Present)

• Designed and deployed scalable microservices integrating ML models using FastAPI and PyTorch for predictive analytics and NLP-driven applications in production.
• Led development of an enterprise financial analytics platform using ML models to improve forecasting accuracy, anomaly detection, and decision-making.
• Built end-to-end MLOps pipelines with MLflow and Weights & Biases, including training, deployment, monitoring, and model lifecycle management.
• Integrated AWS services (Lambda, S3, EC2, RDS) with ML workflows and implemented asynchronous processing using Celery and Redis for real-time inference APIs.
• Mentored a team of 15+ developers and ML engineers in Agile/Scrum environments, driving architecture decisions and delivery of scalable AI systems.

Machine Learning Engineer at Aerotek (2019-03 – 2021-05)

• Developed and deployed end-to-end NLP pipelines using Hugging Face Transformers and spaCy for entity recognition, text classification, and LLM-based applications.
• Automated data preprocessing and feature engineering workflows using Python, Pandas, and NumPy, reducing manual processing time by 50%.
• Built and scaled production ML microservices using FastAPI, Docker, and Kubernetes to support real-time inference and high-availability systems.
• Improved model performance using hyperparameter tuning techniques with Optuna and Ray Tune for deep learning and transformer-based models.
• Deployed ASR (Whisper-based) speech-to-text systems and built monitoring dashboards to track transcription accuracy and system performance.

Software Developer (AI Focus) at Hire With Near (2018-08 – 2019-02)

• Created ML-backed REST APIs for enterprise applications using Python, FastAPI, and PostgreSQL
• Developed data pipelines for structured and unstructured text processing
• Implemented logging and observability for ML service health and performance

Master of Science in Computer Science – George Mason University (2016-03 – 2018-05)