SUMMARY

Currently working as an AI Engineer at Volkswagen(Scania), contributing to real-world AI projects with hands-on experience in deploying and fine-tuning transformer-based models such as BERT, GPT variants, and publicly available LLMs. Skilled in leveraging cloud platforms like AWS, including AWS Bedrock, for scalable AI/ML development. Experienced in implementing MLOps/LLMOps practices for model lifecycle management, automation, and observability. Proficient in orchestrating AI workflows using Kubernetes and building robust NLP and Generative AI solutions.

WORK EXPERIENCE

• AI/ML Consultant: Volkswagen Group Technology Solutions India, Gurugram. (Nov 2024 - Continue)
  • Extensive involvement in end-to-end AI/ML project lifecycles, from problem scoping to development, deployment, and monitoring.
• Principal Consultant: NSE TalentSprint, Hyd. (April 2021 - Oct 2024)
  • Led and coordinated with the academic and operational team
  • Proposed and designed industry-relevant Projects and Assignments in the ML & Generative AI Domain
  • Giving Lecture sessions on selected topics
• Research Fellow: IIT Delhi (March - May, 2019)
  • Project: Energy Efficiency and Occupant Comfort Management in the Built Environment
  • Responsibility: BMS Data Collection, Analysis, and Modeling.
• Assistant Professor: Thapathali Campus, Kathmandu, Nepal (June 2015 – Dec 2016)
• Lecturer: Sagarmatha Engineering College, Kathmandu, Nepal (Nov 2011 – May 2015)

ACADEMIC DETAILS

• M.S. Mech.Eng.(Thermal Science) (CGPA: 8.57/10) - I.I.T. Delhi 2019
• B.E. Mechanical Engineering (70.82%) - T.U. Kathmandu, Nepal 2010

TECHNICAL SKILLS

Machine Learning, MLOps, Deep Learning, CV, NLP: BERT, GPT, ChatGPT, T5, LLMs | Python: NumPy, Pandas, Matplotlib, Scikit-Learn, TensorFlow/Keras, PyTorch, AWS (SageMaker, S3 Cloud9, EC2, ECR-ECS-Fargate), SQL

COURSES (Relevant to DS/ML)

• Computer Programming
• Probability and Statistics
• Numerical Methods
• Linear Algebra
• Differential and Integral Calculus
• Engineering Economics
• Experimental Methods
• Economics & Planning of Energy Systems
• CNN, NN & Deep Learning, Sequence Models

IIT DELHI THESIS

• Title: Performance analysis of an in-situ Data Center
  • Supervisor: Prof. Sanjeev Jain
  • Objectives:
  1. Energy analysis of the data center at IIT, Delhi. (Application of Data Analysis, Machine Learning: Multivariable Regression and Neural Network)
  2. Investigation of airflow management and temperature distribution inside the server room. (Application of Ansys ICEPAK - CFD)
  • Outcome: Identification of Energy Conservation Opportunities.

SCHOLASTIC ACHIEVEMENTS

• Got admission in the Regular category in B. Engineering, Pulchowk Campus.
• Merit-based students, through entrance exams, are selected in this category and get full scholarships throughout four years.
• Got best project award - HVAC domain in MSR project (IIT Delhi) –2018/19

PERSONAL PROJECTS

• Implementation of classical ML:
  • Credit Card Fraud Detection (Imbalance Classification)
  • Loan amount prediction
  • Housing price prediction
• CNN-Transfer Learning for Image Classification and Gradio app hosting on HF spaces
• Image Segmentation: Unet and Deeplab V3+
• BERT fine-tuning for sentiment classification
• RAG-Chat with your document (OpenAI API + Lang Chain)
• Fine-tune GPT2 on your custom dataset for Generative question-answering
• Fine Tune BERT For Extractives Question Answering
• Text Summarization Gradio app deployed on HF spaces
• Time Series Analysis of Sunspot Data
• Sample ML in production (CI): Test Cases and Packaging included

PUBLICATIONS

• Performance Analysis of an in-situ Data Centre: Journal - Energy and Buildings (Elsevier) Feb 2020
• Study on Diesel Fuel Consumption Reduction in Dairy Industries by Application of Solar Thermal Energy. - IOE Graduate Conference, Nov 2013 (Kathmandu, Nepal)