Open to opportunities

Robert Hayes

@roberthayes

Message

Senior AI Engineer building scalable ML, deep learning, and LLM ranking systems.

United States

Message

What I'm looking for

I’m looking to build and scale production AI systems—transformers, RAG, and low-latency inference—with strong MLOps, experimentation, and monitoring. I want to own end-to-end pipelines and deliver measurable impact on ranking and personalization.

I’m a Senior AI Engineer with 13+ years of experience building and scaling machine learning, deep learning, and LLM-based systems. I focus on large-scale recommendation, ranking, and personalization platforms that perform reliably in production.

At Meta, I lead development of production-grade AI systems, including transformer models, retrieval-augmented generation (RAG), and real-time inference pipelines. I architect end-to-end ML pipelines—from data ingestion and feature engineering to distributed training, model evaluation, and deployment for real-time systems.

I specialize in end-to-end ML lifecycle execution: distributed training, MLOps, CI/CD for ML, experiment tracking, A/B testing, model monitoring, and drift detection. I build low-latency serving systems optimized for high-QPS environments using quantization, pruning, caching strategies, and batch inference optimization.

I also drive training-serving parity through feature store architectures and consistent feature computation, while building monitoring for data quality and inference anomaly detection. I mentor ML engineers on distributed systems design and production ML architecture, helping teams deliver measurable improvements in relevance and personalization.

Experience

Work history, roles, and key accomplishments

Current

Senior AI Engineer

Current

Senior Machine Learning Engineer

Machine Learning Engineer

Lead Data Scientist

EPAM Systems

Jun 2015 - Oct 2017 (2 years 4 months)

Led data science initiatives delivering predictive modeling and machine learning solutions for business intelligence, forecasting, and customer analytics. Designed and deployed classification, regression, and clustering models, standardizing end-to-end ML workflows and evaluation while mentoring junior data scientists.

predictive modeling Classification regression Clustering Feature Engineering Hypothesis Testing Cross Validation Model Evaluation Python data transformation

Senior Data Scientist

EPAM Systems

Feb 2014 - Jun 2015 (1 year 4 months)

Developed and deployed machine learning models for predictive analytics, including classification and regression solutions for enterprise use cases. Performed feature engineering and statistical validation, integrated models into production (batch and service-based), and refined algorithms through evaluation and error analysis.

Machine Learning Classification regression Feature Engineering Statistical Analysis Hypothesis Testing Batch Scoring Customer Segmentation

Data Scientist

EPAM Systems

Dec 2012 - Feb 2014 (1 year 2 months)

Built foundational machine learning and statistical models for classification, forecasting, and exploratory analytics across enterprise datasets. Implemented data cleaning and preprocessing, created predictive analytics workflows, and applied hypothesis testing to identify patterns and support customer analytics.

Machine Learning Forecasting Classification Data Cleaning data preprocessing Statistical Methods Hypothesis Testing Predictive Analytics

Data Analyst

EPAM Systems

Jun 2011 - Dec 2012 (1 year 6 months)

Supported data collection, cleaning, and validation to ensure reporting accuracy across structured enterprise datasets. Built and maintained SQL-based queries and reporting datasets, created dashboards, and performed data quality checks and reconciliation to prepare analysis-ready data for modeling.