Akhilesh M

I’m an AI Engineer with 4+ years of experience building and scaling end-to-end machine learning and Generative AI systems in fast-paced startup environments. I’m proud of owning the full lifecycle—from data pipelines and model design to production deployment, evaluation, and monitoring.

At CogitX.ai, I led GenAI and ML initiatives that directly improved business outcomes, including a movie box office prediction system that achieved 90%+ accuracy consistently and improved analysis efficiency by 30%. I also developed a ticket pricing model using elasticity to maximize revenue, and built LLM-powered and semantic search solutions to improve retrieval relevance by 40%.

I focus heavily on production readiness: I operationalized prediction pipelines, engineered an analytics stack for interactive dashboards serving 400+ concurrent users, and architected microservices for consistent daily data ingestion. I scaled cost-efficient scraping infrastructure on AKS using on-demand VMs with concurrent execution and auto-termination, while orchestrating pipelines from scrapers through databases to dashboards.

I enjoy leading and mentoring—I've led a team of 5 developers—and collaborating cross-functionally with product and business to deliver scalable AI solutions. I’ve also established LLMOps pipelines using Azure DevOps and AKS to improve latency and cost efficiency, and built agentic and RAG-based systems for automation, multi-document Q&A, and customer-facing chatbot experiences.