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I'm a Senior AI Engineer with 10+ years of experience designing and deploying machine learning and AI systems across enterprise applications. I specialize in building AI-powered solutions, NLP, LLM-based workflows, and retrieval-augmented generation, delivering measurable improvements in accuracy and response relevance. I'm experienced in integrating ML models into production APIs, optimizing performance and scalability in cloud environments, and leading end-to-end ML lifecycles from data processing to monitoring. I collaborate with multidisciplinary teams to translate business needs into scalable AI architectures and reliable operations.…I'm a Senior AI Engineer with 10+ years of experience designing and deploying machine learning and AI systems across enterprise applications. I specialize in building AI-powered solutions, NLP, LLM-based workflows, and retrieval-augmented generation, delivering measurable improvements in accuracy and response relevance. I'm experienced in integrating ML models into production APIs, optimizing performance and scalability in cloud environments, and leading end-to-end ML lifecycles from data processing to monitoring. I collaborate with multidisciplinary teams to translate business needs into scalable AI architectures and reliable operations.

Arbaaz Meghani

AI Engineer, Data Scientist, Full Stack Developer, +2

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I'm a Senior AI Engineer with 10+ years of experience designing and deploying machine learning and AI systems across enterprise applications. I specialize in building AI-powered solutions, NLP, LLM-based workflows, and retrieval-augmented generation, delivering measurable improvements in accuracy and response relevance. I'm experienced in integrating ML models into production APIs, optimizing performance and scalability in cloud environments, and leading end-to-end ML lifecycles from data processing to monitoring. I collaborate with multidisciplinary teams to translate business needs into scalable AI architectures and reliable operations.…I'm a Senior AI Engineer with 10+ years of experience designing and deploying machine learning and AI systems across enterprise applications. I specialize in building AI-powered solutions, NLP, LLM-based workflows, and retrieval-augmented generation, delivering measurable improvements in accuracy and response relevance. I'm experienced in integrating ML models into production APIs, optimizing performance and scalability in cloud environments, and leading end-to-end ML lifecycles from data processing to monitoring. I collaborate with multidisciplinary teams to translate business needs into scalable AI architectures and reliable operations.

Available to hire

I’m a Senior AI Engineer with 10+ years of experience designing and deploying machine learning and AI systems across enterprise applications. I specialize in building AI-powered solutions, NLP, LLM-based workflows, and retrieval-augmented generation, delivering measurable improvements in accuracy and response relevance.

I’m experienced in integrating ML models into production APIs, optimizing performance and scalability in cloud environments, and leading end-to-end ML lifecycles from data processing to monitoring. I collaborate with multidisciplinary teams to translate business needs into scalable AI architectures and reliable operations.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior AI Engineer at eBay

April 1, 2021 - Present

Led the design and deployment of ML/AI models for marketplace personalization and predictive analytics using Python, TensorFlow, PyTorch, and scikit-learn, achieving a 30% increase in model accuracy at enterprise scale. Developed and fine-tuned large language model–based NLP solutions with Retrieval-Augmented Generation patterns leveraging vector databases and enterprise data sources, improving response relevance by 25%. Built AI-powered applications and services, integrating models into production environments and REST APIs with FastAPI and Spring Boot, reducing inference latency by 30%. Engineered end-to-end data pipelines with Pandas, NumPy, and distributed processing to scale data handling by 35%. Performed hyperparameter tuning, model evaluation, and monitoring to improve reliability to 99.9%. Oversaw the full ML lifecycle from data preprocessing to deployment and monitoring using MLOps pipelines and CI/CD. Collaborated with data engineers and product teams to deliver scalable,

Senior Data/ML Engineer at Optum

February 1, 2019 - March 1, 2021

Designed and implemented end-to-end ML systems supporting healthcare analytics and population health initiatives, improving risk prediction accuracy by 22%. Built distributed data pipelines using Python, SQL, and Apache Spark to process large-scale claims and EHR datasets, reducing processing time by 30%. Developed supervised ML models for risk scoring and anomaly detection using scikit-learn and gradient boosting techniques. Engineered longitudinal feature frameworks incorporating patient history and clinical coding signals to improve model stability and interpretability. Implemented structured validation processes including cross-validation, bias review, calibration testing, and stability checks to meet regulatory scrutiny. Integrated ML outputs into backend services consumed by care management teams, improving operational efficiency by 18%. Deployed batch inference workloads on Azure infrastructure maintaining 99.9% reliability. Introduced Docker containerization reducing environmen

Full Stack/AI Engineer at Tempus AI

February 1, 2016 - December 1, 2018

Contributed to scalable ML pipelines supporting oncology research, cohort analysis, and precision medicine initiatives. Built ETL pipelines processing EHR, genomic metadata, and pathology records in HIPAA-compliant environments improving data standardization accuracy by 30%. Developed supervised ML models for outcome prediction and cohort stratification using scikit-learn and gradient boosting improving predictive performance by 20%. Engineered preprocessing pipelines using Pandas and SQL reducing data inconsistency by 25%. Designed longitudinal feature engineering frameworks improving model interpretability and clinical relevance. Implemented clinical NLP workflows using TF-IDF, rule-based extraction, and domain vocabularies improving information extraction accuracy by 18%. Applied statistical similarity and document representation methods supporting cohort discovery and patient similarity analysis. Established cross-validation, calibration, bias assessment, and stability validation p