About me

4.5+ years of expertise in GenAI, MLOps, and data lifecycle management to diverse sectors. Focused on AI/ML innovation, from data cleaning to production model deployment.

I engineer applications using data intelligence.

Sidharth Rai is an accomplished professional with 4.6 years of technical expertise in data science and machine learning, specializing in GenAI and MLOps. He excels at transforming data insights into robust applications across diverse domains, including healthcare, supply chain, manufacturing, and finance. Sidharth brings hands-on expertise across the entire data lifecycle, from data management (APIs, schema validation, anomaly detection, cleaning, document classification) to model building, deployment, and monitoring. He has a proven track record of building MLOps infrastructure for automation, Data CI/CD pipelines, and implementing A/B testing with comprehensive model monitoring for data drift. His deep experience with LLMs, fine-tuning, OpenAI, LangChain, and Azure AI Speech Services has enabled him to successfully integrate these into GenAI-based chatbots.

 

Before his focus on GenAI, Sidharth honed his skills in collaborative development and optimization, particularly with Microsoft Tools and IBM integration solutions. As a Software Development Engineer, he notably achieved 80% accuracy in sentiment analysis for tweets, showcasing proficiency in research and web design. He also led the development of advanced machine learning models using Python, TensorFlow, and Azure DevOps, ensuring superior performance and scalability. Proficient in containerizing ML applications using Docker for production deployment and configuring open-source services for model versioning, Sidharth’s collaborative approach ensures the development of high-performing and scalable AI solutions.

What I do

From understanding your requirements, designing a blueprint and delivering the final product, I do everything that falls in between these lines.

Agentic AI

Building advanced agentic AI applications to automate complex tasks and enhance decision-making processes.

Data SCIENCE

Crafting insights from data, deploying machine learning models, and diving into computer vision—bridging the gap between raw data and meaningful solutions.

Web Development

Elevating digital presence with WordPress mastery—customized designs, seamless WooCommerce , Shopify integration, and dynamic WordPress layouts using Elementor, for a captivating online experience.

Skills

Generative AI
LLMs, fine-tuning, OpenAI, LangChain, and Azure AI Speech Services 90%
Machine Learning
Time Series, Neural Networks, Deep Learning, Semantics, Azure ML 85%
Cloud Computing
Microsoft Azure, AWS 90%
Python
75%
SQL
MySQL, SSMS, NoSQL 75%
Web Development
WordPress (Elementor, WooCommerce), Shopify 80%

My Experience

April 2025 - Present

Persistent Systems Limited, Gurugram

Lead software engineer

Leading 6 developers, I spearhead MLOps for healthcare AI bias mitigation. My work involved implementing fairness metric tracking, integrating XAI, and building automated retraining pipelines, ultimately improving model fairness by 25%.

Jan 2021 - April 2025

IBM, Gurugram

Data Scientist

Led ML model design with Python, TensorFlow. Collaborated on model optimization, supported deployment, and facilitated career progression from Associate to Lead developer.

Jun 2020 - Dec 2020

Allied Lawyers, Dubai

Software Development Engineer

Researched and gathered requirements for secure messaging app. Developed sentiment analysis system achieving 80% accuracy. Designed graphics, boosting axlev.com's engagement by 30%.

Works

20+

Projects Completed In Last 5 Years

2

Publications

15+

Startups benefitted from consulting

Research Paper

The research published in Social Science Research Network (SSRN), talks about Risk and Return from the movement of stock prices by quantitative analysis. It considers both fundamental and technical analysis. 

The price movement are sometimes low or high depending not only on company businesses but also on company-related news, socio-political conditions, natural disasters, and economic changes. Here we use a novel machine learning approach, designed and implemented to predict the stock market prices.

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