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I'm an AI/ML Engineer with 3+ years of experience building scalable solutions using generative AI, large language models, and NLP. I design agentic systems, document intelligence workflows, and ML pipelines deployed at scale. I’m adept at driving automation and data-backed insights across industries like insurance, sports, and enterprise analytics. I thrive on turning messy data into clean, reproducible models and dashboards, collaborating with cross-functional teams to ship reliable products. I enjoy exploring new AI techniques, keeping systems observable, and delivering value through practical, compliant AI.…I'm an AI/ML Engineer with 3+ years of experience building scalable solutions using generative AI, large language models, and NLP. I design agentic systems, document intelligence workflows, and ML pipelines deployed at scale. I’m adept at driving automation and data-backed insights across industries like insurance, sports, and enterprise analytics. I thrive on turning messy data into clean, reproducible models and dashboards, collaborating with cross-functional teams to ship reliable products. I enjoy exploring new AI techniques, keeping systems observable, and delivering value through practical, compliant AI.

Sanket Muchhala

AI Engineer, Data Scientist, Data Analyst, +2

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I'm an AI/ML Engineer with 3+ years of experience building scalable solutions using generative AI, large language models, and NLP. I design agentic systems, document intelligence workflows, and ML pipelines deployed at scale. I’m adept at driving automation and data-backed insights across industries like insurance, sports, and enterprise analytics. I thrive on turning messy data into clean, reproducible models and dashboards, collaborating with cross-functional teams to ship reliable products. I enjoy exploring new AI techniques, keeping systems observable, and delivering value through practical, compliant AI.…I'm an AI/ML Engineer with 3+ years of experience building scalable solutions using generative AI, large language models, and NLP. I design agentic systems, document intelligence workflows, and ML pipelines deployed at scale. I’m adept at driving automation and data-backed insights across industries like insurance, sports, and enterprise analytics. I thrive on turning messy data into clean, reproducible models and dashboards, collaborating with cross-functional teams to ship reliable products. I enjoy exploring new AI techniques, keeping systems observable, and delivering value through practical, compliant AI.

Available to hire

I’m an AI/ML Engineer with 3+ years of experience building scalable solutions using generative AI, large language models, and NLP. I design agentic systems, document intelligence workflows, and ML pipelines deployed at scale. I’m adept at driving automation and data-backed insights across industries like insurance, sports, and enterprise analytics.

I thrive on turning messy data into clean, reproducible models and dashboards, collaborating with cross-functional teams to ship reliable products. I enjoy exploring new AI techniques, keeping systems observable, and delivering value through practical, compliant AI.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at Progressive Insurance

May 1, 2024 - Present

Engineered custom NLP and CV models using TensorFlow and PyTorch to process and classify claim-related texts, forms, and images. Developed NER and sentiment analysis tools using BERT models via Hugging Face Transformers to extract key entities from claim documents. Built ML pipelines with Apache Airflow and Azure Data Factory to preprocess and stream data from on-prem SQL Server and Azure Data Lake. Deployed models to production using Azure ML Services with MLflow and DVC for versioning. Designed RESTful APIs using FastAPI to integrate predictive models into the core claims processing workflow. Containerized services with Docker and orchestrated deployments on Kubernetes (AKS). Implemented observability using Prometheus and Grafana with Azure dashboards. Achieved 35% reduction in manual claim processing time and 25% improvement in fraud detection accuracy. Collaborated with underwriters and legal/compliance teams to ensure explainability and auditability of ML models.

Research Assistant – Generative AI at Indiana University Bloomington

December 1, 2023 - May 1, 2024

Improved transcription accuracy by 18 points using a GPT-4 RAG pipeline deployed on Big Red 200, processing over 200 hours of sports videos. Reduced latency in chat feature via sentiment-analysis microservice, processing 1M+ messages in near real-time. Automated retraining pipelines using SLURM on HPC systems, cutting manual ETL effort by 6 hours per match. Documented Gen AI workflows, adopted by two graduate cohorts for ongoing sports psychology research.

Data Analyst at IBM, MH, India

September 1, 2020 - June 1, 2022

Led end-to-end development of a churn prediction model using Python and scikit-learn, driving a 20% reduction in customer attrition. Refactored ETL workflows using Azure Data Lake and SQL, improving data availability and cutting processing time by 15%. Built automated data validation pipelines with SQL and Python, raising dashboard reporting accuracy by 18%. Deployed ML models to Azure ML environments with CI/CD support, accelerating release cycles by 25% across internal products. Authored reproducible model documentation and Jupyter-based reports to align analytics delivery with stakeholder needs. Partnered with business analysts and solution architects to prioritize model features based on customer behavior data trends. Introduced versioning standards for ML pipelines and datasets, increasing transparency in model updates and audits. Conducted internal training sessions on Python-based analytics to upskill the team in reusable code modules.