AI Engineer with 1+ years in AI/ML & Data Science
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Nishant is an AI Intern with 1.2 years of experience leading end-to-end AI projects including Invoicely, Edumaniax, and an Agritech solution. He has strong skills in AI, Machine Learning, Backend, and Infrastructure, with expertise in Python, TensorFlow, PyTorch, and cloud platforms like GCP. Nishant has worked on notable projects like Suicidal Ideation prediction, CapsuleNet for GI disease classification, and TumorMapperNet for brain tumor detection, demonstrating proficiency in deep learning model development and deployment.
Indian Institute of Information Technology Ranchi
B.Tech · Computer Science and Engineering with specialization in AI and Data Science
August 1, 2022 – June 30, 2026
Agility AI
AI Intern
February 1, 2025 – May 1, 2026
Ghāziābād, Uttar Pradesh, India
CapsuleNet
June 1, 2026 – June 1, 2026
Worked in a team of 4 to Developed a model for classification of 10 GI diseases based on WCE images. Leveraged EfficientNet B4 to achieve mean auc of 0.67 and accuracy of 88%. Achieved inference time of 15ms on GPU, cutting the diagnosis time by 60%. CapsuleNet model was ranked 14 in a global competition.
View ProjectTumorMapperNet
June 1, 2026 – June 1, 2026
Led a team of 3 to develop a dual-branch deep learning model for brain tumor classification and Segmentation using MRI scans as input. Used Resblocks within a UNET architecture and Tversky Loss Function for segmentation with accuracy of 92%. Developed a high-performance image classifier using DenseNet121, additional dense layers, and optimization techniques (inverted dropouts, initializers, Adam optimizer) with accuracy of 98.8%.
View ProjectSuicidal Ideation
June 1, 2026 – June 1, 2026
The project utilizes an Bi-LSTM with Attention based deep learning model to predict suicide attempt risk, trained on a dataset with over 232,074 data points. Achieved 97.71% training accuracy and 93.72% testing accuracy. Built a text preprocessing pipeline for NLP using BeautifulSoup, NLTK, and regex. Designed a model using BiLSTM and attention mechanism for improved feature extraction and classification.
View ProjectA Scalable Ensemble Machine Learning Pipeline for Robust Financial Fraud Detection
ieee
June 1, 2026 – Present
CapsuleNet: A Deep Learning Model to Classify GI Diseases using EfficientNet-b7
arxiv.org
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects cover diverse applications of AI, from medical imaging to natural language processing and fraud detection, indicating a broad interest and adaptability. The internship at Agility AI, leading multiple end-to-end AI projects, shows a strong alignment with a dynamic, project-driven environment. Participation in global competitions and publications suggests a proactive, results-oriented mindset that would fit well within an innovative tech culture. The specialization in AI and Data Science further reinforces a strong cultural alignment with an AI-focused role.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex AI projects and competitive rankings. Leadership and teamwork are evident from project descriptions. The ability to architect and deploy end-to-end AI solutions suggests good operational fit for an AI Engineer role. The academic background in AI and Data Science, coupled with practical internship experience, indicates a proactive and dedicated work attitude.