AI Engineer with less than a year in AI/ML & Computer Vision
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AI/ML Engineer pursuing M.Sc. Data Science (Integrated) at Amrita Vishwa Vidyapeetham. Experienced in end-to-end machine learning pipelines, computer vision, deep learning model deployment, and full-stack AI application development using Python, Django, React, and LLM APIs. Published researcher in explainable AI with 97%+ accuracy. Seeking an AI/ML internship to build and ship production-grade intelligent systems.
Amrita Vishwa Vidyapeetham
M.Sc. · Data Science
August 1, 2022 – June 30, 2027
Resilience Business Grids LLP (RBG.AI)
Machine Learning and AI Development Intern
November 1, 2024 – June 1, 2025
Chennai, Tamil Nadu, India
Image Generation Using GANs
June 1, 2026 – Present
• Designed and trained a Deep Convolutional GAN (DCGAN) in TensorFlow on the CIFAR-10 dataset for 100+ epochs, generating diverse and realistic images from random noise vectors. • Mitigated mode collapse by applying batch normalisation across all layers and implementing adaptive loss balancing between the generator and discriminator networks. • Benchmarked model performance quantitatively using FID score and qualitative visual inspection across 1,000+ generated samples, validating image diversity and perceptual fidelity.
View ProjectNavigator - AI Desktop Assistant
June 1, 2026 – Present
• Built a production-ready multi-LLM desktop assistant using React, and TypeScript, integrating OpenAI, Anthropic Claude, and Google Gemini APIs to intelligently automate 10+ task workflows including browser control, file management, and document generation. • Architected a modular agent-core monorepo with a custom plugin system enabling plug-and-play addition of new AI agents without modifying core logic; reduced new-agent integration time significantly. • Secured all API keys and sensitive user data using AES-256-GCM encryption; enforced fine-grained permission-based access control to ensure zero credential exposure in local storage. • Integrated speech-to-text transcription and real-time LLM reasoning pipeline for fully hands-free, voice-driven task automation across all supported workflows.
View ProjectSupervised Machine Learning Certification
Coursera
June 1, 2026 – Present
Explainable Ensemble Learning for Android Malware Detection
Unknown
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from a multi-LLM desktop assistant to GANs for image generation, shows a broad interest and adaptability within the AI domain. The internship experience aligns well with an AI Engineer role, focusing on deployment and optimization. Participation in a hackathon and a publication further demonstrate initiative and a proactive learning attitude, which are positive indicators for cultural fit in an innovative environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through project work (e.g., mitigating mode collapse, custom plugin system). Collaboration is evident from the internship description, where they worked with 5+ engineers. The ability to deliver scalable AI solutions within sprint deadlines suggests good time management and operational efficiency. The focus on production-ready systems and secure data handling indicates a responsible and detail-oriented approach.