Help & Supportcareers@gravityer.com
AI Engineer with 3+ years in LLM, RAG & NLP
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
GenAI Machine Learning Engineer with experience in building LLM-based applications, Retrieval-Augmented Generation (RAG), and NLP pipelines. Strong foundation in Machine Learning and Deep Learning, with hands-on experience in developing scalable AI systems, deploying models using FastAPI, and working with cloud platforms like GCP.
SASTRA Deemed University
M.Tech. · Artificial Intelligence and Data Science
August 1, 2020 – June 30, 2022
Anjalai Ammal Mahalingam Engineering College
B.E. · Computer Science and Engineering
August 1, 2015 – June 30, 2019
Insemi Technology Client: Ford
GenAI Engineer
August 1, 2025 – January 1, 2026
India
Barrla Systems
AI Developer
October 1, 2024 – December 1, 2024
India
Cunard Consulting Ltd.
AI Developer
December 1, 2023 – April 1, 2024
India
Ombrulla
Junior Software Engineer (Artificial Intelligence)
February 1, 2023 – December 1, 2023
India
Ford
Associate Intern
February 1, 2022 – October 1, 2022
India
Detecting Sentimental Analysis in Memes using BotNet and Glove
June 24, 2026 – Present
Sentimental Analysis in Memes are detected using various Machine learning algorithms.
Transformer-based semantic similarity model
June 24, 2026 – Present
Developed transformer-based semantic similarity model (0-1 scoring) using Hugging Face. Deployed real-time inference using FastAPI on AWS, enabling scalable text similarity evaluation.
Covid-19 Future Forecasting
June 24, 2026 – Present
To predict upcoming confirm cases, death cases, recovery cases by using various learning algorithms. Support vector machine, Linear Regression, Lasso Regression, Exponential smoothing, Auto Regressive Integrated Moving Average algorithms used.
LLM-based PDF QA system
June 24, 2026 – Present
LLM-based PDF QA system using LangChain and vector database, enabling semantic search over documents and improving answer relevance through optimized chunking and embeddings.
Cultural Fit Analysis
The candidate's project diversity, ranging from sentimental analysis to forecasting and LLM-based QA systems, indicates a broad interest in AI applications. The experience across different companies (Insemi, Barrla, Cunard, Ombrulla) and client engagements (Ford) suggests adaptability to various work environments. The academic background in AI and Data Science further strengthens the fit for an AI Engineer role. The listed personal projects also show initiative and continuous learning.
Soft Skills & Operational Fit
The candidate demonstrates a project-oriented approach, having worked on several AI/ML projects. The experience with CI/CD pipelines (Tekton) and real-time inference deployment suggests an understanding of operationalizing AI models. However, the resume does not provide explicit details on collaboration, problem-solving methodologies, or adaptability, making it difficult to assess soft skills comprehensively.