Machine Learning Engineer with 2+ years in AI/ML & Cloud Solutions
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
A results-driven Machine Learning Engineer and Software Developer with a strong academic foundation (MCA) and hands-on experience in building intelligent, scalable systems. I specialize in backend development, cloud deployment, and advanced AI solutions—including Agentic AI, LLM orchestration, and autonomous agents using LangChain, LangGraph, and CrewAI. I've contributed to high-impact projects such as real-time document parsing, AI chatbots, and predictive modeling pipelines. Skilled in Python, FastAPI, Flask, TensorFlow, Azure, and Databricks, I blend strong coding practices with a deep understanding of data science and MLOps to deliver reliable, production-grade solutions.
MG University
Master of Computer Applications
August 1, 2022 – June 30, 2024
MG University
Bachelor of Science · Physics
August 1, 2019 – June 30, 2022
Candata.ai
Machine Learning Engineer
May 1, 2024 – Present
Bengaluru, Karnataka, India
International Centre For Free and Open Source Software (ICFOSS)
Software Developer
January 1, 2024 – March 1, 2024
Thiruvananthapuram, Kerala, India
Satellite Image Classification using CNN
June 1, 2026 – Present
Designed and implemented a system using CNNs to categorize and analyze satellite imagery.
Railway Management System
June 1, 2026 – Present
Designed and implemented a Railway Management System using linked lists and queues for efficient ticket booking and waiting list management.
Student Management System
June 1, 2026 – Present
Designed and developed a Student Management System to streamline academic record-keeping and administrative tasks.
Hospital Management System
June 1, 2026 – Present
Created an Android application to optimize healthcare processes and improve patient services.
Plagiarism Detection in the Digital Era: A Systematic Review of Tools and Techniques
January 1, 2024 – March 1, 2024
Conducted a systematic review titled "Plagiarism Detection in the Digital Era: A Systematic Review of Tools and Techniques". Evaluated a wide range of tools and techniques for digital plagiarism detection, highlighting their effectiveness, limitations, and advancements. Provided an in-depth analysis of syntactic and semantic level methods used across plagiarism detection systems.
Python for Data Science, AI and Development
Coursera
June 1, 2026 – Present
Python Project for Data Science
Coursera
June 1, 2026 – Present
Introduction to Android Mobile Application Development
Coursera
June 1, 2026 – Present
Bootstrap 5 Course
Udemy
June 1, 2026 – Present
Basic Image Classification with TensorFlow
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects cover diverse areas like image classification, railway management, student management, and hospital management, indicating a broad interest in applying technical skills to various domains. The professional experience at Candata.ai aligns directly with the target role of Machine Learning Engineer, showcasing practical application of advanced AI concepts. The research experience and publication further demonstrate a commitment to learning and contributing to the field. The breadth of technical skills listed (Python, Java, C++, various ML/AI frameworks, cloud services) suggests adaptability and a willingness to explore different technologies, which generally contributes positively to cultural fit in dynamic environments.
Soft Skills & Operational Fit
The candidate's project descriptions and professional experience indicate a focus on problem-solving and system design. The academic projects and research experience suggest an ability to conduct systematic reviews and collaborate on development tasks. The TDD mention in projects, though not elaborated, hints at an understanding of good development practices. However, without direct assessment data, specific soft skills like teamwork, leadership, or communication cannot be definitively evaluated.