Help & Supportcareers@gravityer.com
AI Engineer with 1+ years in Machine Learning and Generative AI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML Engineer with hands-on experience in developing and deploying scalable machine learning, deep learning, and Generative AI solutions using Python, TensorFlow, PyTorch, and Scikit-learn. Skilled in NLP, LLMs, RAG workflows, predictive analytics, and end-to-end AI pipeline development with expertise in Docker, FastAPI, CI/CD, and AWS deployment. Passionate about building intelligent, business-driven AI systems through model optimization, automation, and production-ready ML workflows to deliver impactful real-world solutions.
ATME College of Engineering
Bachelor of Engineering · Computer Science (AI & ML)
August 1, 2022 – June 30, 2026
Maharaja's College
PUC · Science Stream (PCM + Computer Science)
June 1, 2020 – May 31, 2022
DRDO-CASDIC
AI/ML Engineer Intern
December 1, 2025 – May 1, 2026
Bengaluru, Karnataka, India
Cognifyz Technologies
Machine Learning Intern
October 1, 2024 – April 1, 2025
Mumbai, Maharashtra, India
AI Resume Optimization Agent
January 1, 2026 – June 1, 2026
Built an AI-powered Agentic AI resume optimization workflow using n8n, LLMs, and Retrieval-Augmented Generation (RAG) to analyze job descriptions and improve ATS alignment. Implemented prompt engineering, NLP-based keyword extraction, memory-based reasoning, and contextual retrieval techniques to generate role-specific resume enhancements dynamically. Integrated external tools and automated AI workflows for resume refinement, improving keyword matching, content optimization, recruiter visibility, and workflow efficiency.
Hybrid Deep Learning Architecture for 3D Object Detection
January 1, 2025 – December 31, 2025
Developed a hybrid deep learning architecture using PyTorch, ResNet101, and VGG19 for 3D object detection through binary regression techniques. Implemented transfer learning and fine-tuning workflows, achieving an R2 score of 0.96 through optimized training and feature representation strategies.
Jarvis AI – Intelligent Automation Platform
January 1, 2025 – December 31, 2025
Built a production-ready AI-powered virtual assistant using Python, integrating LLMs, speech recognition, text-to-speech, and REST APIs to automate real-world tasks through natural language commands. Designed and implemented 30+ intelligent automation modules spanning communication, web navigation, system utilities, media management, and productivity workflows, enhancing user efficiency through voice-enabled interactions.
PowerSight AI
January 1, 2025 – December 31, 2025
Developed LSTM and Random Forest models for power outage prediction using time-series data. Built and deployed preprocessing and training pipelines on AWS EC2 using Docker and FastAPI. Reduced prediction error by 18% through feature selection and hyperparameter optimization.
Machine Learning
Coursera (Andrew Ng)
June 1, 2026 – Present
Machine Learning with TensorFlow
Infosys Springboard
June 1, 2026 – Present
Python for Artificial Intelligence (AI)
Infosys SpringBoard
June 1, 2026 – Present
CS50P: Introduction to Python
Harvard University
June 1, 2026 – Present
Advanced Machine Learning
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and initiative in AI/ML, ranging from resume optimization to virtual assistants and predictive analytics. This diversity, coupled with internships in both defense and business-oriented ML, suggests adaptability and a broad interest in applying AI across different domains. The focus on building 'intelligent, business-driven AI systems' aligns well with a results-oriented culture. The candidate is still pursuing a bachelor's degree, indicating a strong learning mindset.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted AI solutions, suggesting strong problem-solving and project management skills. The internships highlight collaboration and working under production constraints, which are positive indicators for operational fit. However, without direct behavioral assessment, soft skills like teamwork, communication, and adaptability are inferred from project descriptions and not explicitly evaluated.