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I am a Senior AI/ML Engineer with 10+ years of experience building intelligent systems across healthcare, retail, and engineering domains. I have a strong foundation in machine learning, GenAI, and LLM-driven applications, including Claude, ChatGPT, and Azure OpenAI. I design end-to-end GenAI solutions and AI Agents using Python, data ingestion, embedding pipelines, retrieval logic, and model orchestration. I’ve built scalable LLM-powered applications, leveraging transformer architectures, RAG pipelines, and prompt engineering across Azure OpenAI, AWS Bedrock, and Claude. I work with structured and unstructured data, NLP, embeddings, semantic search, and retrieval to ground outputs in production-grade systems. I also deploy, monitor, and instrument pipelines with Docker, Kubernetes, and cloud services, and I collaborate closely with cross-functional teams to translate business requirements into reliable AI solutions.…I am a Senior AI/ML Engineer with 10+ years of experience building intelligent systems across healthcare, retail, and engineering domains. I have a strong foundation in machine learning, GenAI, and LLM-driven applications, including Claude, ChatGPT, and Azure OpenAI. I design end-to-end GenAI solutions and AI Agents using Python, data ingestion, embedding pipelines, retrieval logic, and model orchestration. I’ve built scalable LLM-powered applications, leveraging transformer architectures, RAG pipelines, and prompt engineering across Azure OpenAI, AWS Bedrock, and Claude. I work with structured and unstructured data, NLP, embeddings, semantic search, and retrieval to ground outputs in production-grade systems. I also deploy, monitor, and instrument pipelines with Docker, Kubernetes, and cloud services, and I collaborate closely with cross-functional teams to translate business requirements into reliable AI solutions.

Abhinaya R

AI Engineer, Data Scientist, AI Developer, +1

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I am a Senior AI/ML Engineer with 10+ years of experience building intelligent systems across healthcare, retail, and engineering domains. I have a strong foundation in machine learning, GenAI, and LLM-driven applications, including Claude, ChatGPT, and Azure OpenAI. I design end-to-end GenAI solutions and AI Agents using Python, data ingestion, embedding pipelines, retrieval logic, and model orchestration. I’ve built scalable LLM-powered applications, leveraging transformer architectures, RAG pipelines, and prompt engineering across Azure OpenAI, AWS Bedrock, and Claude. I work with structured and unstructured data, NLP, embeddings, semantic search, and retrieval to ground outputs in production-grade systems. I also deploy, monitor, and instrument pipelines with Docker, Kubernetes, and cloud services, and I collaborate closely with cross-functional teams to translate business requirements into reliable AI solutions.…I am a Senior AI/ML Engineer with 10+ years of experience building intelligent systems across healthcare, retail, and engineering domains. I have a strong foundation in machine learning, GenAI, and LLM-driven applications, including Claude, ChatGPT, and Azure OpenAI. I design end-to-end GenAI solutions and AI Agents using Python, data ingestion, embedding pipelines, retrieval logic, and model orchestration. I’ve built scalable LLM-powered applications, leveraging transformer architectures, RAG pipelines, and prompt engineering across Azure OpenAI, AWS Bedrock, and Claude. I work with structured and unstructured data, NLP, embeddings, semantic search, and retrieval to ground outputs in production-grade systems. I also deploy, monitor, and instrument pipelines with Docker, Kubernetes, and cloud services, and I collaborate closely with cross-functional teams to translate business requirements into reliable AI solutions.

Available to hire

I am a Senior AI/ML Engineer with 10+ years of experience building intelligent systems across healthcare, retail, and engineering domains. I have a strong foundation in machine learning, GenAI, and LLM-driven applications, including Claude, ChatGPT, and Azure OpenAI.

I design end-to-end GenAI solutions and AI Agents using Python, data ingestion, embedding pipelines, retrieval logic, and model orchestration. I’ve built scalable LLM-powered applications, leveraging transformer architectures, RAG pipelines, and prompt engineering across Azure OpenAI, AWS Bedrock, and Claude. I work with structured and unstructured data, NLP, embeddings, semantic search, and retrieval to ground outputs in production-grade systems. I also deploy, monitor, and instrument pipelines with Docker, Kubernetes, and cloud services, and I collaborate closely with cross-functional teams to translate business requirements into reliable AI solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

GenAI / Machine Learning Engineer at HCA Healthcare

December 1, 2023 - Present

Led development of a GenAI-driven claims analysis platform using Python, LangChain, and Azure OpenAI, Claude Code, achieving ~25% improvement in fraud detection accuracy and processing of unstructured healthcare documents. Architected an LLM-based system with retrieval pipelines, vector search, and microservices to enable contextual understanding of clinical data and real-time decision support in healthcare workflows. Aggregated data from S3, SQL systems, APIs, and documents (PDFs, emails); performed data normalization and PHI masking in HIPAA-compliant pipelines; organized storage across AWS S3, Azure Data Lake, and relational databases. Implemented vector-based retrieval using FAISS and Pinecone for semantic search. Evaluated GPT-based, Claude, and transformer architectures; designed RAG pipelines with embeddings, improved latency via caching; deployed via FastAPI, Docker, Kubernetes. Monitored with Prometheus and Grafana; collaborated with product owners and domain experts to delive

AI / Machine Learning Engineer at Publix Super Markets

October 1, 2022 - November 1, 2023

Developed a demand forecasting system using Python, XGBoost, and time-series models, improving forecast accuracy by ~22% and enabling better inventory planning across multiple retail locations. Selected models (XGBoost, ARIMA, regression) based on needs, balancing accuracy and interpretability. Built an end-to-end ML pipeline (ingestion, feature engineering, training, inference) and aggregated data from SQL systems, APIs, and transactional sources. Engineered features capturing seasonality and promotions; applied cross-validation and hyperparameter tuning. Deployed real-time predictions via FastAPI, containerized with Docker, and orchestrated on Kubernetes; integrated forecasts into operational workflows and dashboards. Strengthened CI/CD with GitHub Actions; monitored model performance and system health to ensure reliability in production.

ML Engineer at State of Delaware

August 1, 2021 - September 1, 2022

Created a clinical prediction system using Python, scikit-learn, and NLP techniques to improve triage accuracy in healthcare workflows. Implemented end-to-end ML workflows (data ingestion, preprocessing, feature engineering, inference) and consolidated structured and unstructured datasets from SQL databases, APIs, and JSON records. Refined data with Pandas and spaCy; designed data validation frameworks and monitoring to detect anomalies and drift. Collaborated with analysts and domain experts to align model outputs with operational needs and regulatory considerations.

Data Scientist at Burns & McDonnell

January 1, 2020 - July 1, 2021

Designed predictive maintenance model using Python, scikit-learn, and XGBoost to reduce unplanned downtime by ~18%. Applied time-series forecasting and classification with feature engineering and hyperparameter tuning for stable predictions across equipment conditions. Owned end-to-end ML workflows from data preparation to model deployment, coordinating with analysts and stakeholders in Agile environments. Consolidated data from SQL databases, APIs, and sensor logs; organized datasets for analytics and ML use cases; implemented scalable data processing with PySpark and Spark/Hadoop, and integrated AI services with enterprise systems via APIs.

Data Engineer at Apple

October 1, 2018 - December 1, 2019

Built scalable data pipelines using Python, PySpark, and SQL to process large volumes of user and system data, reducing processing time by ~30%. Architected distributed data processing with Spark/Hadoop for batch data flows; collaborated with analysts and product managers in Agile environments to deliver high-quality datasets for analytics and ML workflows. Developed ingestion pipelines integrating APIs, SQL databases, and logs; optimized SQL queries and Spark jobs through partitioning and indexing. Ensured reliable data access for reporting, feature engineering, and downstream ML services; worked with cross-platform teams to connect AI services with enterprise systems.

Data Analyst at Value Labs (India)

July 1, 2015 - August 1, 2018

Built a customer reporting solution using Python, SQL, and Excel to analyze sales and CRM data, improving reporting accuracy by ~20% and enabling data-driven decision-making. Created centralized data processing setups, extracted data from SQL databases and flat files, and prepared datasets for dashboards and analytics. Collaborated in Agile teams to understand reporting needs, implemented data cleaning and basic ML experimentation, designed structured tables, and performed basic classification models to support early analytics use cases.