Computer Science and Engineering (Artificial Intelligence) Student | AI/ML and Full-Stack Developer
Computer Science and Engineering (Artificial Intelligence) student with experience building AI systems, Flutter applications, REST APIs, and enterprise virtual assistants.
Rifcare Tech Pvt. Limited
Jan 2025 – Jul 2025 · Gurugram, Haryana
Designed cross-functional collaboration with product managers and backend engineers to deliver scalable Flutter applications, implemented Bloc pattern state management, and reduced widget rebuild cycles by 35%. Mentored 3 junior developers, established CI/CD pipelines using GitHub Actions, and reduced system latency by 40% through optimized API architecture.
Rifcare Tech Pvt. Limited
Jul 2024 – Dec 2024 · Gurugram, Haryana
Engineered cross-platform mobile applications using Flutter, Python, Django, Flask, and Firebase. Developed RESTful APIs with JWT authentication and PostgreSQL optimization, reducing query response time by 50%. Integrated Google Maps API, Firebase Cloud Messaging, and payment SDKs. Delivered an MVP within 3 months using agile methodology and earned a pre-placement offer.
IBM SkillBuild
Jul 2024 – Aug 2024 · Remote, India
Built an enterprise virtual assistant using IBM Watson and Python that resolved 60% of Tier-1 queries and reduced average handling time by 45%. Executed NLP pipelines for intent classification, fine-tuned BERT models, and improved chatbot precision by 15%.
Rifcare
7 mos · Gurugram
- Designed, developed, and deployed machine learning models using Python (scikit-learn, XGBoost, pandas, NumPy) for classification, regression, clustering, and anomaly detection use cases translating model outputs into clear business narratives and actionable recommendations for senior product and business leadership - Developed interactive executive-level dashboards and BI reports providing real-time operational visibility for 500+ users crafting data stories that explained what happened, why it happened, and what actions leadership should take next, going beyond raw reporting to deliver contextual analytical narratives - Applied strong business acumen to frame ML analytics in the context of operational KPIs productivity metrics and business performance drivers ensuring every analytical output was directly connected to a measurable business outcome and decision - Designed and implemented automated data pipelines for enterprise-scale data movement and processing, achieving 50% reduction in query response time and 40% reduction in system latency demonstrating scalable pipeline engineering aligned to modern analytics architecture requirements - Applied ensemble methods (XGBoost, Random Forest), unsupervised clustering (K-Means, DBSCAN), and dimensionality reduction (PCA) to large datasets, uncovering trends, drivers, and predictive insights that supported strategic decision-making - Communicated complex analytical results and ML model insights to non-technical stakeholders and senior leadership through structured presentations, intuitive visualisations, and executive summaries consistently translating analytical complexity into decision-ready business intelligence - Maintained responsible data and AI practices throughout all model development work enforcing data quality controls, documenting model governance, and ensuring analytical outputs adhered to accuracy and integrity standards
Rifcare
6 mos · Gurugram
- Applied advanced analytical techniques and ML models to solve complex business problems, delivering complete end-to-end analytics project within 3-month timeline from data extraction through model deployment to business storytelling earning Pre-Placement Offer for exceptional analytical execution - Built data visualisation and reporting outputs translating quantitative analytical findings into clear, business-relevant insights for non-technical stakeholders demonstrating data storytelling capability aligned to executive audience requirements - Developed Python automation scripts and data pipelines to improve analytics process scalability and reproducibility across business intelligence workstreams
IBM
2 mos
− Built enterprise virtual assistant using IBM Watson and Python, autonomously resolving 60% of Tier-1 queries and reducing average handling time by 45% − Executed NLP pipelines for intent classification, fine-tuning BERT models and optimizing hyperparameters to improve chatbot precision by 15%.
Bachelor of Technology, Computer Science and Engineering (Artificial Intelligence)
Aug 2022 – May 2026
CGPA: 7.14/10
Class XII, PCM
2022
90.6%, CBSE Board
Engineered a synthetic data pipeline using StyleGAN2-ADA to generate 5,000+ MRI samples from fewer than 200 instances. Fine-tuned a Vision Transformer for diagnostic classification, addressed class imbalance using focal loss and oversampling, and deployed an explainable AI module with a Neo4j Knowledge Graph and SHAP interpretability.
Architected a 4-tier cascade system with smart-funnel routing for video streams. Built Tier-2 detection using transfer learning with Xception, achieving 82% validation accuracy, and optimized NVIDIA Tesla T4 GPU training with mixed precision.
Developed an autonomous AI agent using Scrapy and Selenium to collect and synthesize competitor data from more than 1,000 data points. Built predictive analytics models with scikit-learn and XGBoost and integrated Hugging Face Transformers for sentiment analysis, achieving 87% classification accuracy with fine-tuned RoBERTa models.
Dec 19, 2023