--- title: "Mayur K. - Machine Learning Engineer in India | Tal" description: "Meet Mayur K., Machine Learning Engineer @ Rambus | Applied AI/ML | Generative AI, LLMs, RAG & AI Developer Tools based in India. AI stack includes claude, mcp, and n8n. Explore public work links including github and mayurkishorekumar.github.io." image: "https://tal.club/meet/mayur-k/share-image" --- # Mayur K\. on Tal ## Headline Machine Learning Engineer @ Rambus \| Applied AI/ML \| Generative AI, LLMs, RAG & AI Developer Tools ## About I’m a Machine Learning Engineer at Rambus, building production AI/ML systems for real\-world engineering workflows\. At Rambus, I’ve worked across traditional ML, Generative AI, RAG, agentic systems, MCPs, and AI developer tooling, primarily in an enterprise, air\-gapped Linux environment\. My work includes building an ML system for semiconductor EDA resource prediction across 1\.5M\+ production jobs, enterprise RAG systems combining keyword, vector, and knowledge\-graph retrieval, MCP integrations across Jira, Confluence, Jenkins, and ServiceNow, and AI tooling for engineers through GitHub Copilot, Continue\.dev, and terminal\-based agents\. I enjoy taking ambiguous engineering problems, figuring out what actually needs to be solved, and turning them into systems that people can use\. Core: Python · Machine Learning · Generative AI · LLMs · RAG · Agents · MCP · AI Developer Tools · ML Infrastructure ## Location India ## AI stack claude mcp n8n ollama githubcopilot Chroma ## Work experience Machine Learning Engineer at Rambus, Oct 2025 \- Present · 1 yr 1 mo, Bengaluru, ● Built and deployed production ML and AI systems across semiconductor engineering workflows, spanning predictive ML, Generative AI, RAG, agentic systems, MCPs, and developer tooling in an air\-gapped RHEL/Linux environment\. ● Built an end\-to\-end EDA resource prediction system using IBM LSF and Spectre data, scaling the training dataset from 30K to 1\.5M\+ production jobs across 4\+ years; evaluated multiple models and achieved R² ≈ 0\.87 using quantile XGBoost for resource prediction\. ● Designed and deployed an enterprise AI/RAG ecosystem combining BM25 keyword retrieval, vector search, reranking, and knowledge\-graph retrieval, with department\-specific knowledge bases accessible across the organization\. ● Built and deployed \~15 MCPs personally / \~20 across the team for enterprise systems including Jira, Confluence, Jenkins, and ServiceNow, with reusable Python/FastMCP infrastructure serving hundreds of users\. ● Developed AI developer tooling and agentic workflows across GitHub Copilot, Continue\.dev, terminal\-based agents, and OpenClaw, including \~70 engineering skills and integrations for semiconductor workflows\. ● Automated engineering workflows including NetApp filesystem analytics, VS Code extension provisioning, and SFTP\-based semiconductor data pipelines, reducing manual operational work and improving accessibility for engineers\. ● Developed GenAI\-based engineering log analysis and document\-intelligence workflows using LLMs, OCR, and enterprise APIs for troubleshooting and business\-process automation\. ● Helped drive enterprise AI adoption through Level 1 and Level 2 training, with user feedback indicating approximately 40% average time savings across AI\-assisted workflows\. Technologies Used: Python, SQL, PostgreSQL, XGBoost, LightGBM, Scikit\-Learn, Machine Learning, Generative AI, LLMs, RAG, AI Agents, MCP, FastAPI, Docker, Linux/RHEL, GitHub Copilot, Ollama, Groq, ChromaDB, FAISS, OCR Python Engineering Expert at AfterQuery Experts, Mar 2025 \- May 2025 · 3 mos, San Francisco Bay Area, ● Improved the reliability of production Python\-based ML and data\-processing pipelines by debugging runtime and software issues across NumPy, Pandas, and PyTorch, reducing runtime failures by 40%\. ● Developed and maintained end\-to\-end automated testing workflows for production ML and data\-processing systems\. ● Increased automated test coverage from 68% to 92%, improving deployment reliability and reducing onboarding effort for engineering workflows\. Technologies Used: Python, NumPy, Pandas, PyTorch, Automated Testing, ML/Data Pipelines Applied AI Engineer at Humanitarians AI, Sep 2024 \- May 2025 · 9 mos, Boston, MA, ● Designed and implemented 10\+ AI applications from scratch, building custom RAG pipelines and multi\-agent systems without relying on orchestration frameworks\. ● Built end\-to\-end RAG pipelines for patient history retrieval, clinical triage, and patient routing, implementing document ingestion, embedding generation, semantic search, retrieval, reranking, prompt engineering, and prompt orchestration across knowledge bases containing 10K\+ documents\. ● Developed agentic AI systems incorporating planning, memory, tool orchestration, multi\-hop reasoning, debate, routing, evaluation, and autonomous decision\-making workflows for complex clinical decision\-support tasks\. ● Benchmarked transformer\-based language models, embedding models, and vector databases including FAISS and ChromaDB to optimize retrieval quality, inference cost, and deployment performance in low\-resource healthcare environments\. ● Implemented local Ollama and cloud\-based Groq inference services, enabling AI applications to operate across environments with varying connectivity and compute constraints\. Technologies Used: Python, Generative AI, LLMs, RAG, AI Agents, FAISS, ChromaDB, Ollama, Groq, Embeddings, NLP Project Intern at ISRO \- Indian Space Research Organization, Mar 2021 \- May 2021 · 3 mos, India, ● Developed predictive monitoring models using 10\+ years of telemetry data to identify server overheating risks and support proactive anomaly detection\. ● Built monitoring dashboards and alerting workflows to surface potential overheating events and enable earlier intervention\. ● Reduced response time by approximately 30% through predictive monitoring and automated alerting workflows\. Technologies Used: Python, Machine Learning, Time Series/Telemetry Analysis, Anomaly Detection, Data Visualization ## Education Master of Science \- MS, Artificial Intelligence, Northeastern University BE \- Bachelor of Engineering, Computer Science, Dayananda Sagar College of Engineering, BANGALORE ## Public links - github: https://github\.com/MayurKishoreKumar - mayurkishorekumar\.github\.io: https://mayurkishorekumar\.github\.io/ [View the original profile](https://tal.club/meet/mayur-k) ```json { "@context": "https://schema.org", "@graph": [ { "@type": "Person", "@id": "https://tal.club/meet/mayur-k#person", "name": "Mayur K.", "url": "https://tal.club/meet/mayur-k", "image": "https://tal.club/meet/mayur-k/profile-photo.jpg", "description": "Meet Mayur K., Machine Learning Engineer @ Rambus | Applied AI/ML | Generative AI, LLMs, RAG & AI Developer Tools based in India. AI stack includes claude, mcp, and n8n. 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