Machine Learning Engineer with 1+ years in AI & Deep Learning
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Results-driven Computer Science undergraduate specializing in Machine Learning and AI, with 16+ months of research internship experience building end-to-end ML pipelines across computer vision, healthcare AI, and predictive analytics. Proficient in Python, TensorFlow, PyTorch, and OpenCV, with demonstrated ability to develop, train, and evaluate deep learning models for real-world applications. Seeking a full-time role as an ML Engineer, AI Developer, or Data Science Intern to deliver impactful, production-ready AI solutions.
Medi-Caps University, Indore
B.Tech · Computer Science Engineering (ML Specialization)
August 1, 2022 – June 30, 2026
SBN Research
Machine Learning Research Intern (Part-Time)
June 1, 2024 – October 1, 2025
India
Volvo Eicher Commercial Vehicles
IT Intern
March 1, 2024 – March 1, 2024
India
Human Face Emotion Detection
June 1, 2024 – June 1, 2026
Engineered a real-time CNN-based computer vision pipeline to classify 7 facial emotions (happy, sad, angry, fearful, surprised, disgusted, neutral) from live webcam streams using TensorFlow and OpenCV. Achieved ~85% validation accuracy on the FER-2013 dataset; optimized model latency to enable real-time inference at 24+ FPS on standard hardware through architecture tuning and data augmentation.
View ProjectData Augmentation Study – ResNet18 on CIFAR-10
June 1, 2024 – June 1, 2026
Conducted a rigorous comparative study of Mixup and AugMix augmentation strategies on ResNet18 (CIFAR-10), demonstrating up to 3.2% improvement in test accuracy and improved model robustness over the baseline. Built interactive accuracy/loss visualization dashboards using Matplotlib; documented experimental findings with reproducible PyTorch training scripts.
View ProjectAgentic AI
Datagami
June 1, 2026 – Present
Generative AI
DataGami
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects and internship experience demonstrate a strong alignment with the target role of Machine Learning Engineer, particularly in computer vision and deep learning. The diversity of applications (healthcare, safety, emotion detection) shows adaptability and a broad interest in ML domains. The pursuit of certifications in Agentic AI and Generative AI indicates a proactive approach to learning and staying current with emerging technologies, which aligns well with an innovative culture.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experience highlight collaboration in a research environment and structured collaboration with IT teams, indicating good teamwork and communication skills. The focus on reproducible scripts and documentation suggests an organized and detail-oriented approach. However, without specific assessment data on soft skills, this remains an inference.