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AI Engineer with 1+ years in Data Science & Machine Learning
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Data Scientist Intern and Research Assistant with a strong academic background in Data Science and Electronics and Computer Engineering. Proficient in a wide array of AI, Deep Learning, Machine Learning, and Big Data technologies, including LLMs, PyTorch, TensorFlow, Spark, and AWS. Experienced in developing LLM-driven platforms, enhancing malicious URL detection, and building predictive models for academic and influencer recommendation systems.
University of Maryland, College Park
Master of Science · Data Science
August 1, 2025 – June 30, 2027
Indian Institute of Technology, Madras
Diploma · Data Science
August 1, 2023 – June 30, 2025
Amrita Vishwa Vidyapeetham, Bangalore
Bachelor of Technology · Electronics and Computer Engineering
August 1, 2021 – June 30, 2025
Algonomy
Data Scientist Intern
January 1, 2025 – June 1, 2025
Bengaluru, Karnataka, India
Amrita School of Engineering
Research Assistant
August 1, 2023 – May 1, 2025
Bengaluru, Karnataka, India
Immersive Recommendations: Influencers Recommendations Using Machine Learning
January 1, 2025 – January 1, 2025
Created a hybrid recommendation engine combining collaborative filtering and machine learning algorithms to enhance influencer recommendations on diverse social media platform datasets.
Educational Data Mining for Predicting Academic Outcomes Using Ensemble Techniques
January 1, 2025 – January 1, 2025
Built ensemble models using Random Forest, Gradient Boosting, and Stacking to predict academic outcomes from large-scale behavioral data.
Enhancing Malicious URL Detection Using Advanced Machine Learning Techniques
January 1, 2025 – January 1, 2025
Developed XGBoost and CNN-models with deep learning, improving malicious URL detection accuracy by 8%.
Data Analytics
June 1, 2026 – Present
AI Infrastructure and Operations
NVIDIA
June 1, 2026 – Present
Data Science
John Hopkins University
June 1, 2026 – Present
AI Essentials
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internships demonstrate a strong focus on AI/ML applications, aligning well with an AI Engineer role. The diversity of projects (recommendation systems, cybersecurity, educational data mining) and the breadth of technical skills listed (from LLMs to MLOps) suggest adaptability and a willingness to explore different problem domains. The pursuit of multiple degrees and certifications indicates a proactive learning attitude. However, the experience is primarily academic and internship-based, which might require some adjustment to a fast-paced industry environment.
Soft Skills & Operational Fit
The candidate's project descriptions and experience highlight problem-solving skills, particularly in optimizing processes and improving model accuracy. The academic background and research publications suggest a strong aptitude for analytical thinking and independent work. However, without specific psychometric or English test results, it is difficult to assess communication clarity, work attitude, stress handling, or team collaboration skills.