Open to opportunities

Abbas Syed

@abbassyed

Senior machine learning engineer building scalable, production-ready AI systems across NLP, computer vision, and generative LLMs.

United States

Message

What I'm looking for

I’m looking for a role where I can lead production ML/MLOps, ship LLM and real-time AI with measurable impact, and strengthen teams through experimentation, monitoring/drift detection, and mentorship across cross-functional partners.

I’m a Senior Machine Learning Engineer with 9+ years of experience designing, developing, and deploying production-scale AI systems across NLP, Computer Vision, and Generative AI. I focus on end-to-end ML pipelines, real-time inference services, and LLM-powered applications optimized for performance, scalability, and reliability.

Most recently, I led RAG-based LLM pipelines to automate patient query resolution, improving accuracy by 38% and reducing response time across hospital departments. I also built low-latency multimodal medical AI inference (sub-100ms P95) and developed readmission and chronic condition forecasting, lowering preventable readmissions by 18%, while overhauling HIPAA-compliant MLOps using MLflow, Airflow, and Kubernetes with monitoring and drift detection.

I’m also known for applied experimentation and technical leadership—driving A/B testing, statistical validation, explainable AI, and bias detection—while mentoring engineers and translating research-driven insights into high-impact AI products.

Experience

Work history, roles, and key accomplishments

Current

Lead Machine Learning Engineer

Current

Medicare Solutions LLC

Dec 2023 - Present (2 years 6 months)

Designed and deployed RAG-based LLM pipelines to automate patient query resolution, improving accuracy by 38% and reducing response time. Built sub-100ms P95 multimodal inference services and reduced preventable readmissions by 18% while overhauling HIPAA-compliant MLOps with MLflow, Airflow, and Kubernetes.

RAG Triton Inference Server fastAPI MLFlow Airflow Kubernetes A B Testing Model Monitoring

Senior Data Scientist

MindsDB

Aug 2020 - Nov 2023 (3 years 3 months)

Built real-time fraud detection and risk scoring models using XGBoost, LightGBM, and deep learning ensembles, reducing financial losses by 22%. Deployed models with Docker, Kubernetes, and MLflow and improved production deployment time by 40% while maintaining automated monitoring and drift detection.

XGBoost LightGBM Docker Kubernetes MLFlow Apache Kafka Spark Model Monitoring Power BI

Machine Learning Engineer

Feedzai

May 2017 - Jul 2020 (3 years 2 months)

Developed recommendation and churn prediction models, increasing user retention by 15% and boosting customer lifetime value. Built end-to-end ML pipelines with Pandas, Dask, SQL, and Spark, and improved dataset quality with schema checks and anomaly alerts using Great Expectations.