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AI Research Engineer with 1+ years in Agentic AI & Deep Learning
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Assessing your cultural and operational fit
ML Engineer specializing in Agentic AI, Computer Vision, and custom deep learning architectures. Proven experience building multi-agent systems, spatial-temporal graph neural networks, and deploying low-latency microservices. Published AI researcher and copyright holder focused on building autonomous systems that solve unstructured data challenges.
Christ University
Bachelor of Technology · AI & Machine Learning
August 1, 2022 – June 30, 2026
BrandContext
MLOps Intern
November 1, 2025 – Present
India
Roamyo
AI/ML Intern
April 1, 2025 – June 1, 2025
India
Intel Corporation
Project Intern
May 1, 2024 – July 1, 2024
India
Deep Research Agentic System
June 1, 2026 – Present
Built a hierarchical agent swarm where 'Planner', 'Researcher', and 'Reviewer' agents collaborate for deep-dive web synthesis. Integrated Tavily API for high-precision information retrieval, enabling the system to generate cited, research-grade reports.
View ProjectSynthetic Data Engine using WGAN-GP
June 1, 2026 – Present
Engineered a Wasserstein GAN with Gradient Penalty (WGAN-GP) to generate high-fidelity synthetic tabular data for predictive maintenance. Implemented a robust evaluation pipeline using t-SNE to visualize manifold alignment and minimized Wasserstein distance metrics.
View ProjectTemporal GNN for Autonomous Vehicles
June 1, 2026 – Present
Engineered a Temporal Graph Attention Network (TemporalGNN) to classify driving events (e.g., collision risks) by processing sequences of ego-centric scene graphs over 3-second windows. Transformed raw NuScenes dataset inputs into directed graphs, embedding relative velocities, yaw rates, and spatial displacements as complex edge attributes for multi-head attention.
View ProjectGenerative AI with LLMs
DeepLearning.AI
June 1, 2026 – Present
Data Science for Engineers
NPTEL - IIT Madras
June 1, 2026 – Present
A Low Complexity Patch Based Approach to Image Super Resolution
Springer LNNS (SCOPUS)
January 1, 2026 – Present
Three-Level Secure Automated Gate System
Govt. of India Copyright L-141525/2024
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio (agentic systems, GANs, GNNs, super-resolution) and internships across different companies (BrandContext, Roamyo, Intel) demonstrate adaptability and a broad interest in various AI domains. Their leadership roles and participation in technical communities suggest a collaborative mindset and a willingness to contribute beyond individual tasks, aligning well with a dynamic research environment. The focus on autonomous systems and unstructured data challenges aligns directly with the target role's potential demands.
Soft Skills & Operational Fit
The candidate's leadership roles (Technical Lead, Student Secretary, Class Representative) suggest strong communication, teamwork, and organizational skills. Their involvement in orchestrating technical workshops indicates a proactive approach to knowledge sharing and community building. The project descriptions are clear and detailed, reflecting good written communication.