Siemens · UP, India
Skills: React, Python, Docker, CI/CD
Company Overview
Siemens EDA is a global technology leader in Electronic Design Automation software. Our software tools enable companies around the world to develop highly innovative electronic products faster and more cost-effectively. Our customers use our tools to push the boundaries of technology and physics to deliver better products in the increasingly complex world of chip, board, and system design.
Position Overview
We are seeking a talented and versatile AI / Machine Learning Engineer with 3–10 years of experience to design, build, and deploy production-grade AI-powered capabilities across our electronic design and verification tools. In this hands-on engineering role, you will contribute to the design and implementation of AI/ML pipelines and Agentic AI systems, bridge modern GenAI architectures with robust software engineering, and integrate intelligent capabilities directly into engineering workflows. Collaborating closely with domain experts, software architects, and product teams, you will translate cutting-edge AI concepts—such as intelligent copilots, multi-step reasoning agents, and automated EDA verification assistants—into reliable, scalable, and high-impact solutions.
Key Responsibilities
Design, implement, and deploy end-to-end AI/ML and Agentic AI solutions integrated into EDA software workflows and developer environments. Build and enhance intelligent agent systems capable of automated reasoning, planning, multi-step execution, and tool usage using modern frameworks (LangGraph, Model Context Protocol / MCP, etc.). Develop and optimize production Retrieval-Augmented Generation (RAG) pipelines, leveraging vector databases, hybrid retrieval, metadata filtering, and semantic reranking. Build robust data preprocessing, feature extraction, model inference, and evaluation pipelines adhering to clean code, testability, and CI/CD practices. Work closely with domain experts (chip design, verification), product managers, and core software engineering teams to…
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