J.P. Morgan - Software Engineering Job Simulation

Python for Data Science

Data Analysis with Python

Advanced Learning Algorithms

Supervised Machine Learning: Regression and Classification

AWS Educate Machine Learning Foundations

Machine Learning Specialization

Data Analytics with Python

Unsupervised Learning, Recommenders, Reinforcement Learning

Agentforce Specialist

Bachelor of Technology - BTech

• Led student-focused technology initiatives as a Google Student Ambassador, engaging and mentoring a large student community.
• Organized and spearheaded technical events, including Hack with Gemini, encouraging students to explore AI and emerging technologies.
• Conducted technical talks, workshops, and interactive sessions to help students learn, build, and participate in developer activities.
• Coordinated with student teams and campus communities to execute events, drive participation, and foster a collaborative technology ecosystem.

Google Student Ambassador

I worked on a project titled Predictive Analytics in Healthcare Using Machine Learning for Disease Prediction. In this project, I utilized the PIMA dataset to perform data cleaning and analysis, followed by data visualization. I implemented machine learning models such as Support Vector Machines (SVM), Random Forest, and Long Short-Term Memory (LSTM) networks. After evaluating model performance using metrics like accuracy, Random Forest emerged as the best-performing model. This project helped me deepen my understanding of machine learning techniques in the healthcare domain.

Artifical Intelligence and Machine Learning Intern

Fellow

• Engineered LLM-powered automation systems using Python, Playwright/CDP, browser-use, and agentic workflows to automate complex enterprise processes across third-party platforms.
• Built scalable backend and distributed processing services with FastAPI, PostgreSQL, Celery, Redis, Docker, and AWS, supporting concurrent workloads and production-oriented automation.
• Optimized AI and browser-automation pipelines through concurrency, caching, connection pooling, retries, circuit breakers, resource management, and autoscaling.
• Developed ERP data-processing and forensic analytics pipelines spanning 13 layers, 14 business modules, and 160+ automated tests for detecting financial and operational anomalies.
• Worked across LLMs, RAG, OCR, document processing, REST APIs, data engineering, cloud infrastructure, and AI automation, contributing to end-to-end enterprise AI solutions.

AI Intern

AI Engineer

github

Know about srijith Chetla's work experience, education, and much more. srijith Chetla