💬Data is how we listen to reality, but data science is how we translate what we hear into something we can understand💡

About Me

🌱 An MBA finance and engineering graduate with a passion for addressing pressing global challenges and building innovative & sustainable AI solutions.
😎 Proficient in designing and deploying end-to-end ML architecture using Cloud & MLOps.

🔘 Get in touch with me 👇 🔘

📁GitHub	✉️akash.mathur2289@gmail.com
✍️Medium	🏢LinkedIn
#️⃣Kaggle	🤗Space

🛠️Generative AI Applications 👨🏽‍💻

Professional Experience

CGI, Amsterdam, Netherlands

Senior ML Engineer (Sep 2024 – Present)

Achieved 60% faster proposal responses by engineering a RAG system with agentic memory, tools, and custom prompts, accelerating RFI evaluations and enabling quicker sales decisions.
Transformed data discovery by designing a hybrid search engine with LLM-powered re-ranking, reducing time to insights by 50% and making global data platform more intuitive and user-centric.
Leveraged LLMs to generate task-specific synthetic data using PyTorch, enhancing model performance and reducing bias in AI systems.
Implemented medallion architecture to build scalable pipelines that cleaned, enriched, and secured unstructured data, making them auditable and AI-ready.

S&P Global, Gurugram, India

Senior ML Engineer – Automotive Supply Chain Technology & Aftermarket (Jun 2021 – Aug 2024)

Generated $500k+ in revenue by architecting end-to-end product on AWS that forecast Vehicles Scrappage. Setup Feature store and model monitoring with SageMaker to track and analyze metrics.
Automated model deployment and serving with FastAPI through an efficient CI/CD integrated serverless workflow using AWS, Docker, Terraform and GitHub.
Reduced daily news processing time by 80% by architecting end-to-end application on AWS. It recommends top news articles through similarity search and summaries generated from a fine-tuned FLAN-T5 model.
Improved customer satisfaction and product quality by employing sentiment analysis using a fine-tuned RoBERTa model and identifying prevalent issues using topic modelling via BERTopic on AWS.

Bank of America – Gurugram, India

Assistant Manager - Quantitative Modelling (Nov 2018 – Jun 2021)

Improved bank’s risk and capital management by forecasting Equities Trading Account Profit revenue using Linear Regression as a part of regulatory compliance.
Reduced monthly processing time by 90% by designing ETL pipelines tailored for large-scale data and leveraging ARIMA for revenue forecasting using Databricks.
Demonstrated proficiency in Information Extraction from disparate sources and utilizing advanced analytical techniques and algorithms to make it actionable for stakeholders.

Credit Suisse – Pune, India

Analyst, Advanced Analytics - Global Markets Technology (May 2015 – Nov 2018)

Enhanced the bank’s risk management practices by designing ETL pipelines, enabling precise identification of high-risk hedge fund investors with the Random Forest classifier.
Optimized product offerings by 40% through segmentation using Dimensionality Reduction and Clustering Techniques to identify distinct client groups, leading to deeper customer understanding.

Generative AI Applications

Repository

Developed versatile applications powered by Large Language Model (LLM), including conversational AI chatbot, semantic search and text summarization, coupled with UI creation using LangChain and LlamaIndex.
Implemented fine-tuning strategies in RAG applications, optimizing both ingestion (chunking, metadata, multi-indexing) and inferencing (query transformations, advanced retrieval strategies, re-ranking) stages for enhanced performance.

1. Conversational AI (Chatbot 🤖) with RAG using LangChain🦜️ & LlamaIndex🦙

Comprehensive Guide to Customize your Llama2 ChatBot using LlamaIndex and Streamlit [Medium, GitHub]
Mistral-7B-Instruct Based Multi-PDFs ChatBot using LangChain and Streamlit [GitHub]
Llama2-7B Based CSV ChatBot using LangChain [GitHub]
Simple Chatbot using AWS Bedrock [GitHub]

2. Advanced RAG📚📒

Optimizing Retrieval with Additional Context & MetaData using LlamaIndex [Medium, GitHub]
Enhancing Retrieval Efficiency through Evaluating Reranker Models using LlamaIndex [Medium, GitHub]
Query Augmentation for Next-Level Search using LlamaIndex [Medium, GitHub]
Smart Tracking and Debugging of Document Changes using LlamaIndex [Medium, GitHub]

3. LLM Fine Tuning 🧠 and Applications 💡

Elevating Mistral-7B’s Performance through Finetuning using QLoRA [Medium, GitHub]
T5 Fine Tuning & Evaluation for Text Summarization [GitHub]
Falcon-7B Based Video 🎬 Summarization using Langchain [GitHub]
🎵Audio Generation🎹 using Audio Craft [GitHub]

4. Model Serving and Deployment ☁️

Serverless Magic with Lambda, SageMaker DLC, and API Gateway [Medium, GitHub]
Deploy a Serverless ML Inference using FastAPI, AWS Lambda, and API Gateway [Medium], [GitHub]
Vector Indexing and ANN using FAISS with AWS Serverless Architecture [Medium, GitHub]

5. AWS Serverless Architectures for Big Data Workloads📊

Optimizing Concurrent Batch Jobs Execution [Medium, GitHub]
Effortless Scalability using Asynchronous Lambda Invocation [Medium, GitHub]
Big Data Processing Using Distributed Maps and Step Functions [Medium, GitHub]

Technical Skills

🔝 Technologies	🔝 Interests
• Languages: Python, SQL, Spark • Machine Learning: Scikit-Learn, PyTorch, LangChain, LlamaIndex, Faiss, NumPy, Pandas, MLflow, TensorFlow, NLTK, spaCy, OpenCV • Cloud: AWS (SageMaker, Lambda, Batch, Step Functions, ECS, ECR, API Gateway, S3), Azure (Machine Learning, Data Factory, Databricks, DevOps), • MLOps: BentoML, MLflow, DVC, Docker, Terraform, CI/CD, Git, GitHub Actions • Visualization: Tableau, Power BI • Database: MySQL, SQLite, Vector Databases	• Generative AI • NLP • Recommendation Systems • MLOps • Stock Market Analysis, Macroeconomics • Swimming, Yoga, Meditation, Cooking

🔝 Technologies

🔝 Interests

• Languages: Python, SQL, Spark
• Machine Learning: Scikit-Learn, PyTorch, LangChain, LlamaIndex, Faiss, NumPy, Pandas, MLflow, TensorFlow, NLTK, spaCy, OpenCV
• Cloud: AWS (SageMaker, Lambda, Batch, Step Functions, ECS, ECR, API Gateway, S3), Azure (Machine Learning, Data Factory, Databricks, DevOps),
• MLOps: BentoML, MLflow, DVC, Docker, Terraform, CI/CD, Git, GitHub Actions
• Visualization: Tableau, Power BI
• Database: MySQL, SQLite, Vector Databases

• Generative AI
• NLP
• Recommendation Systems
• MLOps
• Stock Market Analysis, Macroeconomics
• Swimming, Yoga, Meditation, Cooking

Education

Post Graduate Diploma in Management - Financial Services K J Somaiya Institute of Management, Mumbai, India 2013-2015
Bachelor of Technology - Electronics & Communication Rajasthan Technical University, India 2008-2012