
AI Engineer with less than a year in Machine Learning & NLP
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with strong expertise in Python, ML, Deep Learning, and Data Science. Hands-on experience building and deploying scalable AI systems using TensorFlow, PyTorch, and NLP techniques, including LLMs and Generative AI.
SRH University Of Berlin
Master of Science (M.Sc) · Computer Science
January 1, 2022 – January 1, 2024
PSG College Of Arts and Sciences
B.Sc · Computer Technology
January 1, 2019 – January 1, 2022
AI Engineer - Internship
AI Engineer - Internship
February 1, 2024 – May 1, 2024
Berlin, Berlin, Germany
Public Art Lab
Data Engineer - Internship
March 1, 2023 – September 1, 2023
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Tamil NLP-Based Student Support Chatbot using Deep Learning
February 1, 2024 – May 1, 2024
Built an AI-powered educational chatbot using Python, Flask, PyTorch, and NLP to automate student support services. Leveraged Transformer embeddings and intent classification models to accurately answer admission, course, and fee-related queries through a web-based interface.
Task Management System | Flask, PostgreSQL
May 1, 2023 – June 1, 2023
Engineered a full-stack task management platform featuring user authentication, CRUD operations, and real-time task updates. Leveraged Flask (backend), PostgreSQL (database), and Pandas (data manipulation) for a responsive, scalable, and data-consistent application.
Cultural Fit Analysis
The candidate's academic projects (NLP Chatbot, Task Management System) and internships (AI Engineer, Data Engineer) demonstrate a breadth of technical interests and a willingness to apply learned skills in different contexts. The focus on AI/ML aligns well with an AI Engineer role. The academic background from SRH University of Berlin suggests exposure to diverse educational environments. However, the overall experience is limited to internships and academic projects, which might require more structured mentorship in a full-time role.
Soft Skills & Operational Fit
The candidate's project descriptions and internship roles suggest an ability to work on complex technical problems and contribute to actionable insights. The mention of collaborating in agile environments indicates a potential for good team integration. However, without direct assessment data, specific soft skills like stress handling, communication clarity, or detailed work attitude cannot be definitively evaluated.