Poornima Tagaram

Boston

Summary

A results-oriented Machine Learning Engineer pursuing a Master's in Applied Machine Intelligence, focused on developing and implementing state-of-the-art algorithms for large-scale applications. Experienced in the end-to-end ML workflow, from processing complex datasets to training and evaluating deep learning models in Python using PyTorch, TensorFlow, and JAX. Eager to contribute to challenging AI problems and collaborate on building robust, scalable systems.

Overview

years of professional experience

Work History

ServiceNow Developer

ServiceNow

Boston

08.2025 - Current

Developed and implemented ServiceNow modules to streamline IT service management processes.
Collaborated with cross-functional teams to gather requirements and enhance system functionality.
Customized workflows and forms to improve user experience and operational efficiency.
Assisted in troubleshooting and resolving technical issues within the ServiceNow platform.

Research Assistant, Pedestrian Transit Accessibility

Massachusetts Institute of Technology (MIT)

06.2025 - Current

Developing and evaluating deep learning models (YOLOv8, Mask R-CNN) to analyze large-scale urban imagery datasets, achieving 92% detection accuracy.
Implementing novel computer vision algorithms and contributing to a scalable data processing pipeline, reducing manual data handling by over 80%.
Collaborating with a cross-functional research team on open-source tools aimed for publication, focusing on improving transit accessibility in developing urban systems.

Full Stack Web Developer

Mosh E-com Services Pvt Ltd

11.2023 - 10.2024

Developed production-level code for a high-traffic e-commerce platform with 99.7% uptime.
Engineered scalable data pipelines for processing customer logs, enabling analytics that informed data-driven business strategy.

Education

Master of Science - Applied Machine Intelligence

Northeastern University

Boston, MA

05.2026

Skills

Languages: Python, SQL, JavaScript
AI/ML Frameworks: TensorFlow, PyTorch, JAX, Scikit-learn

AI/ML Concepts: Deep Learning, Computer Vision, NLP, Recommender Systems, Unsupervised Learning
Data & MLOps: Large-Scale Data Processing (Spark, Pandas), Docker, Git, CI/CD, API Integration

Websites

Publications

Co-Author: Real-Time Smart Transformer Design Based on IoT, IEEE TEMSMET Conference 2023. Contributed to research exploring IoT applications for infrastructure improvement.
Research Assistant Participant: Contributed to a user research study evaluating digital health education tools, providing feedback on interface usability and patient-centered design.

Timeline