{"id":3449292,"url":"https://alion.io/job/siemens-software-engineer-aiml","title":"Software Engineer - AI/ML","company":{"id":131,"name":"Siemens","domain":"siemens.com","url":"https://alion.io/company/siemens","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Avature","truth_index":{"grade":"A","score":100,"open_postings":18,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":11,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":17000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":32},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"gRPC","optional":false},{"name":"Hugging Face","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Transformers","optional":false},{"name":"Axolotl","optional":true},{"name":"C++","optional":true},{"name":"CUDA","optional":true},{"name":"DeepEval","optional":true},{"name":"Fine-tuning","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"LoRA","optional":true},{"name":"MLFlow","optional":true},{"name":"Neo4j","optional":true},{"name":"PEFT","optional":true},{"name":"QLoRA","optional":true},{"name":"Ragas","optional":true},{"name":"SystemVerilog","optional":true},{"name":"TRL","optional":true},{"name":"TruLens","optional":true},{"name":"Weights & Biases","optional":true}],"status":"live","first_seen_at":"2026-10-29T10:15:35Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-02T08:43:58Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Company Overview\nSiemens 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.\nPosition Overview\nWe 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.\nKey Responsibilities\nDesign, implement, and deploy end-to-end AI/ML and Agentic AI solutions integrated into EDA software workflows and developer environments.\nBuild 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.).\nDevelop and optimize production Retrieval-Augmented Generation (RAG) pipelines, leveraging vector databases, hybrid retrieval, metadata filtering, and semantic reranking.\nBuild robust data preprocessing, feature extraction, model inference, and evaluation pipelines adhering to clean code, testability, and CI/CD practices.\nWork closely with domain experts (chip design, verification), product managers, and core software engineering teams to formulate AI use cases, prototype solutions rapidly, and harden them into production.\nEnsure robust model safety, evaluation against hallucinations, prompt injection defenses, IP protection, and compliance with enterprise security and governance standards.\nQualifications\n3 to 10 years of professional software engineering and AI/ML experience, with proven hands-on involvement in taking AI/ML or LLM-based solutions from concept to production.\nStrong proficiency in Python with solid fundamentals in data structures, algorithms, object-oriented design, modular architecture, and automated testing (pytest, CI/CD).\nSolid understanding of ML fundamentals, deep learning architectures (Transformers, CNNs/GNNs), feature engineering, data preprocessing, and model evaluation metrics.\nPractical experience building applications with foundational LLMs (OpenAI, Claude, LLaMA, etc.), prompt engineering best practices, and Agentic design patterns (ReAct, plan-and-execute, tool calling).\nHands-on experience implementing RAG systems, embedding models, vector databases, and semantic retrieval strategies.\nProficiency with modern ML and AI development libraries such as PyTorch, Hugging Face Transformers, Scikit-learn, LangChain, or LangGraph.\nFamiliarity with containerization (Docker), REST/gRPC API development (e.g., FastAPI), and model serving/evaluation workflows.\nDemonstrated ability to break down complex domain problems, rapidly prototype AI solutions, benchmark performance, and iterate toward production-quality implementations.\nPreferred & Good-to-Have Skills\nHands-on experience with Parameter-Efficient Fine-Tuning (PEFT, LoRA, QLoRA), instruction tuning, dataset preparation/curation, or domain-specific model adaptation using Hugging Face TRL or Axolotl.\nFamiliarity with graph databases (e.g., Neo4j, Apache AGE) and knowledge graph-augmented retrieval.\nFamiliarity with C/C++, compiler concepts, or GPU profiling/acceleration (CUDA).\nBackground or curiosity in digital logic design, SystemVerilog, hardware verification, or Electronic Design Automation (EDA) tools.\nHands-on experience with LLM evaluation frameworks (e.g., Ragas, TruLens, DeepEval) and experiment tracking platforms (MLflow, Weights & Biases).\nWhy Us\nWe are Siemens:\nAt Siemens Software, flexibility is how we work-hybrid by default, built on trust and autonomy. Together, 30,000 people across more than 200 countries build technology that shapes the real world.\nYou'll grow through real projects, strong technical peers, and global mobility, backed by the scale and benefits of an industrial software leader. We're committed to equality and inclusion, and we hire based on merit, skills, and impact. Bring your curiosity and creativity and help us shape tomorrow!\nDiversity & Inclusion\nWe are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We are committed to building a diverse and inclusive workforce and welcome applications from all qualified candidates.\nSiemens Software. 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