Rohit Gupta

Bengaluru, India 0+ yrs exp 71 · Very Good

About

Computer Science graduate with experience in AI engineering, machine learning, data analytics, and software development through industry internships and research. Skilled in building AI applications, RAG systems, multi-agent workflows, OCR solutions, and backend services using Python and modern AI frameworks. First-author IEEE publication with a strong foundation in deep learning, NLP, computer vision, and scalable software engineering.

Skills & Expertise (46)

Python Advanced

8.5/10

Years Exp

Pandas Advanced

8.0/10

Years Exp

Deep Learning Advanced

8.0/10

Years Exp

NumPy Advanced

8.0/10

Years Exp

Data Pipelines Advanced

8.0/10

Years Exp

Feature Engineering Advanced

8.0/10

Years Exp

Keras Intermediate

7.5/10

Years Exp

Data Cleaning Intermediate

7.5/10

Years Exp

Tableau Intermediate

7.5/10

Years Exp

TensorFlow Intermediate

7.5/10

Years Exp

Model Evaluation Intermediate

7.5/10

Years Exp

SQL Intermediate

7.5/10

Years Exp

scikit-learn Intermediate

7.0/10

Years Exp

Git Intermediate

7.0/10

Years Exp

Hyperparameter Optimization Intermediate

7.0/10

Years Exp

Exploratory data analysis Intermediate

7.0/10

Years Exp

NLP Intermediate

7.0/10

Years Exp

Docker Intermediate

6.5/10

Years Exp

Document AI OCR Vision Transformers Image Classification Exploratory Data Analysis (EDA Transfer Learning Model Versioning Experiment Tracking MLOps Fundamentals MLflow Claude C++ Statistical Modeling PyTorch Large Language Models LangChain LangGraph LlamaIndex Hugging Face Transformers Postgresql Prompt Engineering AI Agents Retrieval-Augmented Generation Semantic Search Attention Mechanisms LLM Evaluation FAISS Pinecone

Work Experience

Software Engineering Intern - Data & Analytics

Viasat India

Feb 2026 - Apr 2026

Worked as a Software Engineering Intern within the Data & Analytics team, developing data-driven solutions that transformed complex customer data into actionable business insights. Designed and implemented an end-to-end analytics pipeline to integrate data from multiple sources into a unified, analysis-ready dataset, significantly reducing manual data preparation efforts. Developed customer segmentation, scoring, and ranking models using feature engineering and normalized metrics to identify high-value accounts and support targeted business strategies. Built interactive Tableau dashboards that enabled stakeholders to perform self-service analytics, accelerating decision-making and improving operational efficiency. Key Contributions Built an end-to-end analytics pipeline integrating data from multiple sources. Developed customer segmentation, scoring, and ranking models using Python. Applied feature engineering and data preprocessing techniques to improve analytical accuracy. Created interactive Tableau dashboards for business intelligence and stakeholder reporting. Automated data preparation workflows to reduce manual effort. Collaborated with cross-functional teams to deliver data-driven business solutions. Technologies: Python, SQL, Pandas, Tableau, Data Analytics, Feature Engineering, Business Intelligence

Summer Research Intern - Two Higgs Doublet Model Exploration

IIT Gandhinagar

May 2024 - Jul 2024

Project: Two Higgs Doublet Model (2HDM) Exploration Job Description Conducted machine learning research focused on applying deep learning techniques to particle physics parameter constraint prediction. Processed and analyzed high-dimensional scientific datasets containing over 500,000 records each, applying data preprocessing, balancing, and feature engineering techniques to improve model performance. Designed and trained neural network models with regularization and dropout, achieving a 15% improvement in prediction accuracy over baseline approaches. Produced statistical analyses and research visualizations that contributed to scientific understanding and supported data-driven research outcomes. Key Contributions Processed and analyzed 25 high-dimensional scientific datasets (500K+ rows each). Performed feature engineering and data balancing on large-scale datasets. Designed and optimized deep neural networks using regularization and dropout. Improved prediction accuracy by 15% compared to baseline models. Created statistical visualizations and research reports for scientific analysis. Applied machine learning techniques to computational physics research. Technologies: Python, TensorFlow, Machine Learning, Deep Learning, Neural Networks, NumPy, Pandas, Matplotlib, Data Visualization, Scientific Computing