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ML Engineer with less than a year in AI/ML model development and deep learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated AI/ML Intern with 0.4 years of hands-on experience in training Large Language Models (LLMs) and implementing Transformer-based architectures. Proficient in Python, TensorFlow, and PyTorch, with a strong foundation in deep learning techniques for image classification and natural language processing. Eager to apply technical skills and problem-solving abilities to develop and optimize innovative AI solutions.
Sri Siddhartha Institute of Technology, Tumakuru
Bachelor of CSE · Computer Science and Engineering
September 1, 2022 – July 1, 2026
G.D. DAV Public School, Bhandarkola
Class XII (CBSE)
May 1, 2020 – May 1, 2022
Saint Francis School Jasidih
Class X (ICSE)
June 1, 2019 – April 1, 2020
Zieers Private Limited
AI/ML Intern
February 1, 2026 – Present
India
CNN model in Alexnet using google colab
June 1, 2026 – Present
Implemented a CNN model based on AlexNet architecture for image classification tasks using Python Performed data preprocessing including resizing, normalization, and augmentation in Google Colab Trained the model using deep learning frameworks like TensorFlow/PyTorch and optimized hyperparameters Evaluated model performance using accuracy metrics and improved results through tuning techniques
Law LLM
June 1, 2026 – Present
Worked on training a Large Language Model (LLM) from scratch using deep learning techniques. Performed data collection, preprocessing, and tokenization on large-scale text datasets and Implemented Transformer-based architecture with embeddings and attention mechanisms. Evaluated and optimized model performance through tuning and fine-tuning methods
Smart Blood Group Detection
June 1, 2026 – Present
Developed a machine learning to detect the blood group using image processing technique by using python. Implemented feature extraction and classification algorithms to improve prediction accuracy and reduce manual errors. Designed a user-friendly interface for real-time sample upload and instant result display for laboratory assistance.
IEEE Volunteer
IEEE
June 1, 2026 – Present
Proj Expo & CHILL
Unknown
June 1, 2026 – Present
Hackathon
Unknown
June 1, 2026 – Present
The candidate scored only 12% on the Data Scientist - Artificial Intelligence test, indicating a very weak understanding of the core concepts and practical application required for this role.
Limitations
The candidate achieved a high score of 90% on the Data Engineer - Azure test, demonstrating strong proficiency in Azure-specific data engineering, including Databricks DLT, streaming, and cost management.
Cultural Fit Analysis
The candidate's academic projects and internship show a clear interest in AI/ML, aligning with the target ML Engineer role. Participation in a hackathon and IEEE volunteer activities indicates a proactive and collaborative spirit. However, the experience is primarily academic and internship-level, which might require mentorship for integration into a senior professional environment.
Soft Skills & Operational Fit
The psychometric test score of 237/500 suggests potential areas for development in logical reasoning, work attitude, stress handling, and team collaboration. The English test score of 54/100 indicates a need for improvement in communication clarity and professional language usage.
Strengths
Limitations