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ML Engineer with less than a year in ML Systems & Python
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer with expertise in designing, building, and deploying scalable ML systems for real-world applications. Specializes in Python, TensorFlow, PyTorch, and Scikit-learn, with a strong foundation in algorithms, data structures, and software engineering best practices. Experienced in developing robust data pipelines, feature engineering, and model optimization, as well as productionizing ML solutions using Docker, Kubernetes, and cloud ML platforms. Adept at implementing MLOps workflows including CI/CD, model versioning, and monitoring. Proven ability to collaborate with cross-functional teams, communicate technical concepts effectively, and deliver high-impact, reliable AI solutions.
S.A. Engineering College, Chennai
Master of Computer Applications (MCA) · Computer Applications
August 1, 2023 – June 30, 2025
ST Hindu College, Nagercoil
Bachelor of Science (B.Sc) · Computer Science
August 1, 2020 – June 30, 2023
KENFRA Research Solutions
Programmer Intern
June 1, 2025 – July 31, 2025
Kanniyakumari, Tamil Nadu, India
DocuSphere
January 1, 2025 – June 1, 2026
• Architected a RAG-based AI document assistant utilizing Python, FAISS, and Sentence Transformers, enabling semantic search and context-aware question answering at scale. • Built scalable data ingestion and preprocessing modules to handle unstructured document data, improving feature extraction and search efficiency. • Integrated Gemini AI for dynamic response generation and deployed the system using Docker containers for production readiness. • Implemented model monitoring and logging to track inference accuracy and system health. • Developed a Streamlit interface with persistent chat history using SQLite, supporting multi-user access.
TechZone
January 1, 2025 – June 1, 2026
• Engineered a full-stack e-commerce platform using Flask, delivering robust product catalog, shopping cart, and secure authentication modules. • Designed and deployed RESTful APIs and SQL database integration with automated data validation pipelines. • Orchestrated deployment with Docker and Gunicorn, optimizing resource utilization and system throughput for production environments. • Implemented CI/CD pipelines for seamless updates and integrated monitoring for uptime and performance. • Enhanced frontend with responsive design and real-time email verification using Gmail SMTP.
Cultural Fit Analysis
The candidate's projects demonstrate a proactive and innovative approach, particularly with the RAG-based AI assistant and the e-commerce platform. The breadth of technologies used (Python, various databases, cloud ML platforms, frontend frameworks) indicates a willingness to learn and adapt. The internship experience in a research solutions company aligns well with a problem-solving and continuous improvement culture. The target role of ML Engineer is well-aligned with the candidate's stated skills and project focus.
Soft Skills & Operational Fit
The candidate's project descriptions highlight collaboration within Agile teams, code reviews, and problem-solving, suggesting a good operational fit. The professional summary also emphasizes effective communication and delivering high-impact solutions. However, without direct assessment data, these are inferred from self-reported project contributions.