Open to opportunities

Gulam Baig

@gulambaig

Message

Senior AI/ML engineer delivering scalable, compliant ML solutions that drive measurable business impact.

United States

Message

What I'm looking for

I seek senior roles building production-ready, compliant AI/ML systems with strong MLOps, cross-functional collaboration, and opportunities to mentor and drive measurable business impact.

I am a Senior AI/Machine Learning Engineer with nine years of experience building end-to-end AI/ML solutions across Healthcare, FinTech, software products, and IT services. I design, train, deploy, and scale machine learning and deep learning models using Python, R, TensorFlow, PyTorch and industry MLOps tools to deliver measurable improvements in production systems.

My work has improved clinical and business outcomes—examples include boosting patient risk prediction accuracy by ~42%, improving diagnostic imaging and report classification accuracy by ~47%, and reducing model training and deployment times through automated pipelines. I have deep experience in NLP, computer vision, time-series forecasting, recommendation systems, feature engineering, model interpretability, and continuous monitoring in production.

I prioritize secure, compliant, and reliable AI (HIPAA, HL7, FHIR) and apply cloud and MLOps best practices (AWS SageMaker, GCP Vertex AI, MLflow, Airflow, Docker, Kubernetes) to ensure scalable, observable systems. I collaborate with cross-functional teams, mentor junior engineers, and focus on delivering business value through robust, production-ready ML solutions.

Experience

Work history, roles, and key accomplishments

Current

Senior AI/ML Engineer

Current

Zoll Medical

Aug 2023 - Present (2 years 7 months)

Designed and deployed end-to-end AI/ML solutions for EHR/EMR clinical datasets, improving patient risk prediction accuracy by ~42% and reducing model training time by ~37% through automated pipelines.

Python TensorFlow PyTorch AWS Sagemaker MLFlow Apache Airflow Docker Kubernetes NLP

Software Developer - AI/ML

Hexagon

Jul 2020 - Jul 2023 (3 years)

Designed and implemented end-to-end AI/ML features for enterprise software products, improving model accuracy by 35–45% and reducing feature delivery time by ~30% through scalable pipelines and MLOps.

Python TensorFlow PyTorch XGBoost Apache Airflow Kubeflow Docker Kubernetes Spark

AI/Machine Learning Engineer

Inspira Financial

Apr 2018 - Jun 2020 (2 years 2 months)

Built and deployed ML solutions for financial datasets, improving fraud detection accuracy by ~38% and reducing false positives by ~42% with automated model pipelines and real-time inference.

Python XGBoost LightGBM AWS Sagemaker MLFlow Docker SQL Time Series

Machine Learning Engineer

LexisNexis

Oct 2016 - Mar 2018 (1 year 5 months)

Developed pipelines to convert regulatory PDFs to structured formats and built NLP models for document processing, reducing manual effort by ~40% and improving data extraction accuracy by ~30%.