Open to opportunities

Hamza Aly

@hamzaaly

Message

I lead AI/ML teams building scalable LLM and MLOps systems with business impact.

United States

Message

What I'm looking for

I’m looking to own end-to-end AI/ML delivery—LLMs/RAG, scalable MLOps, and reliable deployment—while partnering cross-functionally to turn business goals into measurable impact, and mentoring teams through clean, production-ready system design.

I’m a Lead AI/ML Engineer with 10+ years of experience building and scaling production-grade machine learning systems, including 4+ years leading teams and owning end-to-end AI strategy.

I architect and deliver large-scale AI platforms processing 50M+ records/day, with proven outcomes like 40%+ automation gains and 30% cost reductions. I’m known for translating complex, ambiguous business problems into scalable, production-ready AI solutions.

My work spans LLMs, RAG architectures, and modern MLOps—engineering RAG pipelines and intelligent copilots, building low-latency vector search, and delivering real-time and batch inference with strong reliability.

I’m a strong advocate for clean system design, reliable deployment, and practical, business-focused innovation. I mentor engineers, influence product direction, and partner cross-functionally to define AI roadmaps and prioritize high-impact use cases.

Experience

Work history, roles, and key accomplishments

Current

Lead AI/ML Engineer

Current

Ramp

Oct 2023 - Present (2 years 8 months)

Led a team of 6+ ML engineers to architect and deploy an enterprise AI platform processing 50M+ records/day on AWS. Delivered 40% automation gains and reduced cloud costs 30% by building RAG-based copilots, low-latency model serving (<100ms), and an end-to-end MLOps/monitoring framework that cut deployment cycle time 60%.

Python RAG Pyspark AWS Sagemaker Kubernetes MLFlow CI CD Model Monitoring

Senior AI/ML Engineer

Flaire

Nov 2018 - Oct 2023 (4 years 11 months)

Developed and deployed NLP models (BERT/Transformers), improving classification accuracy by 25%. Built production recommendations and ML pipelines, increasing engagement/retention by 30% and reducing model inference latency by 40%.

NLP BERT Transformers Recommendation Systems Feature Engineering PyTorch Model Serving Data Pipelines Optimization

Machine Learning Engineer

Flexport

Dec 2016 - Nov 2018 (1 year 11 months)

Developed machine learning models for fraud detection and churn prediction, achieving AUC > 0.90 and improving model accuracy by 20% using tuning and ensemble methods. Built real-time streaming pipelines with Kafka/Spark Streaming and deployed models on AzureML with automated retraining and monitoring.

Python Kafka Feature Engineering Hyperparameter Tuning

Data Scientist / AI Engineer

dbt Labs

Feb 2015 - Dec 2016 (1 year 10 months)

Built regression, classification, and clustering models for forecasting/analytics use cases, improving model performance by 20% via feature selection and hyperparameter tuning. Designed and deployed a production RAG chatbot (FAISS/Pinecone) and evaluation framework, reducing customer support costs by 35% while improving answer relevance and system latency.

Python RAG REST APIs Evaluation(Precision Latency)Kafka