Open to opportunities

Hamza Diego

@hamzadiego

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Senior Machine Learning Engineer & MLOps architect specializing in cloud-native AI solutions.

United States

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What I'm looking for

I seek senior roles building production-grade, cloud-native ML systems with strong MLOps, collaboration, and growth opportunities in healthcare or enterprise AI.

I am a Senior Machine Learning Engineer and applied AI researcher with 13+ years of experience building scalable ML pipelines, production models, and applied research solutions across healthcare, industrial automation, and enterprise domains.

I design and deploy cloud-native MLOps systems using Kubernetes, Docker, MLflow, and experiment tracking (Weights & Biases, TensorBoard), and I have led end-to-end model development from data pipelines to real-time inference and monitoring.

My technical work spans deep learning (PyTorch, TensorFlow, Keras), NLP (Hugging Face, SpaCy, transformers), computer vision (YOLO, CNNs, 3D object detection), reinforcement learning (PPO, SAC, DDPG), and large-scale data engineering (Airflow, Spark, BigQuery, Databricks).

I have significant cloud experience across AWS, Azure, and GCP, plus domain experience delivering HIPAA-compliant healthcare solutions, building AutoML and model catalogs, and mentoring engineers to adopt MLOps best practices.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

Klarity Labs

May 2024 - Present (1 year 6 months)

Designed and deployed LLM and transformer-based NLP models and cloud-native ML APIs, implemented real-time inference monitoring and automated retraining pipelines, and integrated HIPAA-compliant AI patient engagement solutions.

PyTorch Hugging Face fastAPI Docker AWS Lambda MLFlow Grafana Prometheus Reinforcement Learning

Machine Learning Engineer

Tech Innovate Solutions

Feb 2021 - Apr 2024 (3 years 2 months)

Developed recommendation, classification, and regression models, managed distributed training across AWS/GCP with autoscaling, and built ETL pipelines and MLflow-backed experimentation for customer-facing applications.

PyTorch scikit learn AWS GCP Airflow SQL MLFlow Distributed Training MLOps

Machine Learning Engineer

Zesty AI

Jan 2019 - Dec 2020 (1 year 11 months)

Built time-series forecasting and feature-engineered models for operational optimization, created MLOps pipelines with AzureML/Databricks/AKS, and implemented model explainability and responsible AI tooling.

Databricks AKS ARIMA SHAP LIME Explainable AI Reinforcement Learning

AI Developer

NextGen Analytics

Mar 2012 - Dec 2018 (6 years 9 months)

Developed computer vision models (YOLO, CNNs) and OCR pipelines for industrial defect detection, packaged models as microservices with Flask/Docker, and prototyped perception and sensor-fusion systems.