ATHARVAKA
Engineering practical AI systems, from models to deployment.
I am an AI and Machine Learning Engineer focused on building, evaluating, and deploying LLM-powered applications. My work spans model fine-tuning, retrieval-augmented generation, multi-agent systems, and backend engineering.
I focus on turning AI capabilities into measurable outcomes: reliable workflows, efficient asynchronous processing, and deployable services. I work across the stack, from model adaptation and agent orchestration to APIs, data systems, and cloud infrastructure.
Agentic AI
Multi-agent workflows with LangGraph, tool integration, structured outputs, and evaluation-driven improvements.
LLM Fine-tuning
Adapting transformer models with LoRA and QLoRA, then evaluating inference quality and output reliability.
AI Infrastructure
Asynchronous Python services, FastAPI APIs, data integrations, and parallel processing pipelines.
Cloud Deployment
Containerized AI applications and repeatable cloud infrastructure using AWS, Azure, Docker, and Terraform.
TECHNICAL ARSENAL
Professional Experience
AI Engineer Intern
Built an AI product scoring and enhancement engine using parallel product and image pipelines, reducing batch processing time by 80%. Led development of an MCP-powered analytics agent with parallel tool execution, cutting query turnaround time by 55%.
AI & Machine Learning Engineer Intern
Engineered EMG gesture & EEG movement detection models with optimized preprocessing pipelines, achieving production-ready signal classification across 2 real-time applications.
Hackathon Participant & Winner
Won the AWS Build an Agent Challenge 2026, ranking among the Top 100. Also placed in the Top 15 at the Google Gemini 3 Hackathon 2026.
works
Certifications & Achievements
Let's build practical AI systems that deliver.
Open to AI engineering opportunities and collaborations across agentic AI, LLM applications, and production systems.