Help & Supportcareers@gravityer.com
AI/ML Engineer with 2+ years in LLM Systems & MLOps
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Production-focused AI/ML Engineer with hands-on experience architecting scalable LLM systems, ML microservices, RAG pipelines, and agentic AI workflows for production environments. Built and deployed AI systems including recommendation engines, multimodal moderation pipelines, persistent-memory chatbots, face liveness systems, and hybrid retrieval architectures. Experienced in PEFT/LoRA fine-tuning, quantization techniques (PTQ/QAT), inference optimization, knowledge distillation, GPU/CPU serving pipelines, and distributed AI infrastructure. Strong background in LangGraph orchestration, HuggingFace ecosystem, Qdrant vector search, MLOps pipelines, Dockerized deployments, and async Python systems.
Vignan's Foundation for Science, Technology and Research, Guntur
MCA · Data Science
August 1, 2023 – June 30, 2025
Emilo - Social Media Platform
AI/ML Engineer
October 1, 2025 – Present
India
NexGenEdutech
Founder & AI Trainer
April 1, 2025 – Present
India
Datapro Computers, Visakhapatnam
Software Developer
February 1, 2024 – March 1, 2025
Visakhapatnam, Andhra Pradesh, India
Learning Tree, Visakhapatnam
Web Developer
March 1, 2023 – January 1, 2024
Visakhapatnam, Andhra Pradesh, India
LangGraph Multi-Model Agentic Chatbot
June 1, 2026 – Present
• Built an agentic AI chatbot with LangGraph workflows, multi-model routing, and persistent conversational memory. • Implemented asynchronous SQLite-based chat memory using aiosqlite with multi-session conversation management. • Developed streaming response pipelines with tool calling, intent classification, and specialized LLM routing workflows. • Integrated DuckDuckGo search tools and dynamic model selection for coding, writing, and general conversational tasks.
View ProjectLORA Fine-Tuned GPT-2 for Customer Support
June 1, 2026 – Present
• Fine-tuned GPT-2 using PEFT/LoRA on 26K+ customer support instruction-response pairs. • Built intent-aware structured response generation pipelines across 27 customer support intents. • Optimized parameter-efficient training workflows for domain-specific conversational AI generation. • Improved response consistency and intent alignment using structured prompting and domain-conditioned generation.
View ProjectMental Health Depression Prediction - MLOps Pipeline
June 1, 2026 – Present
• Built an end-to-end MLOps pipeline using Airflow, MLflow, Docker, and DVC. • Implemented experiment tracking, model registry, hyperparameter optimization, and automated evaluation. • Developed reproducible ML workflows with containerized training pipelines. • Applied stratified data processing and imbalance-aware optimization using F1-macro evaluation strategies.
View ProjectMahabharata RAG System
June 1, 2026 – Present
• Built a production-grade hybrid RAG pipeline using dense + sparse retrieval with Reciprocal Rank Fusion (RRF). • Developed structure-aware chunking and optimized Qdrant HNSW retrieval pipelines. • Implemented custom RAG evaluation metrics including faithfulness and context precision. • Built streaming response workflows with source-aware retrieval and section-level citation generation.
View ProjectMERN Stack Certification
Unknown
June 1, 2026 – Present
Data Science and Machine Learning (Basic to Advanced)
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including personal projects and a founder role, indicates a proactive and self-driven individual. The focus on production AI engineering aligns well with a target role requiring practical, deployable solutions. The breadth of skills from full-stack development to advanced AI/ML suggests adaptability and a continuous learning mindset, which are positive indicators for cultural fit in a dynamic tech environment.
Soft Skills & Operational Fit
The candidate's project descriptions and professional experience demonstrate strong problem-solving skills, particularly in optimizing complex AI systems for performance and cost. The 'Founder & AI Trainer' role suggests leadership and mentoring abilities. The detailed descriptions indicate a structured approach to development and a focus on production-readiness.