Open to opportunities

RaNa AhMaD

@ranaahmad3

Message

Senior AI/ML engineer building scalable GenAI and MLOps for measurable impact.

United States

Message

What I'm looking for

I’m looking for a team where I can build end-to-end GenAI (RAG/LLM pipelines) with strong MLOps—cost, latency, and drift monitoring included—delivering measurable outcomes while operating in privacy/compliance-first environments.

I’m a Senior AI/ML Engineer and Data Scientist with 13+ years building, deploying, and scaling machine learning, deep learning, and Generative AI end-to-end. I combine deep modeling with production MLOps discipline to ship reliable, high-throughput AI systems.

In recent roles, I’ve led enterprise Retrieval-Augmented Generation (RAG) and Knowledge Graph architectures over 8M+ documents, improving retrieval recall from 71% to 92% and reducing analysis time by 70%. I also architected prompt privacy and secure ingestion pipelines (OCR, STT, and LLM workflows), plus AI governance frameworks for PII/CUI/FCI detection in HIPAA-/SOC 2-aligned environments.

I focus on experimentation and measurable business outcomes—delivering $18M annualized revenue impact, 40% inference-cost reduction, and 5x serving throughput gains. I mentor teams (e.g., leading 9 engineers), set ML engineering and governance standards across product groups, and continuously optimize drift monitoring, data quality, and distributed serving.

Experience

Work history, roles, and key accomplishments

Current

Senior Staff AI/ML Engineer

Current

Alphabridge

Jan 2021 - Present (5 years 5 months)

Designed and implemented enterprise RAG and knowledge graph architectures over 8M+ documents, improving retrieval recall from 71% to 92% and reducing document analysis time by 70%. Built distributed AI serving infrastructure handling 12,000 req/s at 38ms p99 and reduced per-inference cost by 40% via INT8 quantization and predictive autoscaling.

Retrieval Augmented Generation (RAG)Knowledge Graphs Neo4j Kubernetes Prompt Privacy PII Governance

Lead Data Scientist

Borcelle Technologies

Mar 2017 - Dec 2020 (3 years 9 months)

Architected and scaled an enterprise AI/ML platform supporting 40+ production models, cutting deployment cycles from 2 weeks to 2 days and reducing model drift incidents by 55%. Built production NLP and forecasting systems, improving classification F1 from 0.78 to 0.89, increasing forecast accuracy by 33%, and delivering $4.1M+ in operational savings.

Feast Feature Store MLFlow CI CD Transformer NLP (BERT RoBERTa)Terraform Kubernetes Time Series Forecasting (DeepAR TFT Prophet)

Machine Learning Engineer

Capgemini

Jun 2013 - Feb 2017 (3 years 8 months)

Engineered real-time streaming ML systems with Kafka and Spark Structured Streaming for fraud detection, improving recall by 18% while maintaining stable false-positive rates and preventing ~$6.5M in annual fraud losses. Built end-to-end ETL and MLOps pipelines with Airflow and Spark to automate feature engineering, retraining, and multi-environment model deployment.

Kafka Spark Structured Streaming Fraud Detection XGBoost scikit learn Airflow MLOps