ROICY VINU

MLOps Engineer

https://talent.gravityer.com/roicy-vinu

MLOps Engineer with 1+ years in AI/ML & Cloud

Altos Technologies

Key Strengths

Demonstrated experience in end-to-end AI system deployment, including feature engineering, model deployment, monitoring, versioning, and CI/CD rollout.
Proficiency in MLOps practices, including Docker, AWS (EC2, RDS), Jenkins CI/CD, Git, and model versioning, which directly aligns with the target MLOps Engineer role.
Strong background in LLMs and Generative AI, with practical experience in RAG pipelines, prompt engineering, and using models like LLaMA 3 and Qwen2.5-Coder.
Experience with various ML/DL frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers) and computer vision/OCR technologies (OpenCV, Tesseract, PaddleOCR).
Proven ability to lead junior developers and deliver production-grade AI applications with measurable impact (e.g., 70% reduction in HR screening, 92% OCR accuracy).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's diverse project portfolio, ranging from AI debugging assistants to social platforms with AI integration, indicates a broad interest in technology and adaptability. The experience in deploying various AI applications across different domains (HR, banking, biometrics) suggests a versatile mindset. The academic background combined with practical experience shows a commitment to continuous learning and application, which generally aligns well with innovative and fast-paced technical cultures.

Soft Skills & Operational Fit

The candidate's resume highlights leadership in guiding junior developers and a focus on delivering production-ready solutions, indicating strong operational fit and potential for mentorship. The project descriptions demonstrate problem-solving skills and an understanding of real-world application challenges. The emphasis on CI/CD and monitoring suggests a proactive approach to maintaining system health and reliability.

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Assessing your cultural and operational fit

About

AI/ML Engineer with 1+ year of production experience shipping 10+ end-to-end AI systems at Altos Technologies - spanning LLM orchestration, RAG pipelines, OCR, biometrics, and computer vision. Reduced HR screening by ~70% using LLAMA-3.3-70B, achieved ~92% extraction accuracy on scanned banking documents, and deployed a biometric e-voting system for 500+ concurrent users. Skilled in MLOps: model deployment, monitoring, CI/CD, and AWS. Targeting roles in Kochi, Trivandrum, Bangalore, or Remote.

Top Skills

gpt-4Data Pipelines

Education

Marian College Kuttikanam, Idukki

Master of Computer Applications (MCA)

August 1, 2023 – June 30, 2025

St. Antony's College Peruvanthanam

Bachelor of Computer Applications (BCA)

August 1, 2020 – June 30, 2023

Experience

Altos Technologies

Machine Learning Developer

May 1, 2025 – May 1, 2026

Cochin, Kerala, India

Neyndra Global Solutions

AI/ML Intern

December 1, 2024 – February 1, 2025

Thiruvananthapuram, Kerala, India

Projects

AI Debugging Assistant

June 1, 2026 – June 1, 2026

RAG pipeline ingesting codebase ZIPs into FAISS with language-aware chunking; context-aware fixes via Qwen2.5-Coder 1.5B. Async FastAPI REST API; reduced debug turnaround by ~40% across 15+ test repos.

View Project

Picstagram & TextWave

June 1, 2026 – June 1, 2026

Full-stack social platforms with real-time WebSocket messaging, AI chatbot integration, Docker containerisation, and Jenkins CI/CD on AWS EC2 with zero-downtime rolling updates.

View Project

Certifications

IBM Cognitive Class: Data Analysis with Python

IBM Cognitive Class

June 1, 2026 – Present

Machine Learning with Python

IBM Cognitive Class

June 1, 2026 – Present

Deep Learning Fundamentals

IBM Cognitive Class

June 1, 2026 – Present

Key Strengths

Demonstrated experience in end-to-end AI system deployment, including feature engineering, model deployment, monitoring, versioning, and CI/CD rollout.
Proficiency in MLOps practices, including Docker, AWS (EC2, RDS), Jenkins CI/CD, Git, and model versioning, which directly aligns with the target MLOps Engineer role.
Strong background in LLMs and Generative AI, with practical experience in RAG pipelines, prompt engineering, and using models like LLaMA 3 and Qwen2.5-Coder.
Experience with various ML/DL frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers) and computer vision/OCR technologies (OpenCV, Tesseract, PaddleOCR).
Proven ability to lead junior developers and deliver production-grade AI applications with measurable impact (e.g., 70% reduction in HR screening, 92% OCR accuracy).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit