Software Engineer - AI/ML

Job Title

Software Engineer - AI/ML

Role Summary

Hands-on AI/ML engineer building production-grade AI capabilities integrated into electronic design and verification (EDA) software and engineering workflows. Work with domain experts, software architects, and product teams to design, prototype, and harden intelligent assistants, agentic systems, and RAG pipelines for engineering use cases.

Experience Level

Mid-level - 3 to 10 years of professional software engineering and AI/ML experience.

Responsibilities

Deliver end-to-end AI solutions integrated into EDA tools and developer environments; collaborate with cross-functional teams to productionize models and agentic systems.

• Design, implement, and deploy AI/ML and Agentic AI solutions within EDA workflows and developer tools.
• Develop intelligent agent systems for multi-step reasoning, planning, and tool usage using modern frameworks.
• Build and optimize production Retrieval-Augmented Generation (RAG) pipelines with vector DBs, hybrid retrieval, metadata filtering, and semantic reranking.
• Create robust data preprocessing, feature extraction, inference, and evaluation pipelines following testability and CI/CD practices.
• Work with chip design and verification experts to identify AI use cases, prototype solutions, and transition prototypes to production-quality systems.
• Implement model safety measures, evaluate hallucinations, protect IP, and follow enterprise security and governance standards.

Requirements

Must-have technical skills and experience required to perform the role; preferred items listed separately.

• Must-have: 3–10 years building and shipping AI/ML or LLM-based solutions to production.
• Strong Python skills; solid foundations in data structures, algorithms, OOP, modular design, and automated testing (pytest, CI/CD).
• Understanding of ML fundamentals and deep learning architectures (Transformers, CNNs/GNNs); experience with feature engineering, preprocessing, and evaluation metrics.
• Practical experience with foundational LLMs (OpenAI, Claude, LLaMA, etc.), prompt engineering, and agentic design patterns (ReAct, plan-and-execute, tool calling).
• Hands-on experience implementing RAG systems, embedding models, vector databases, and semantic retrieval strategies.
• Familiarity with ML libraries and frameworks such as PyTorch, Hugging Face Transformers, Scikit-learn, LangChain or LangGraph.
• Experience with containerization (Docker), REST/gRPC API development (e.g., FastAPI), and model serving/evaluation workflows.
• Ability to prototype rapidly, benchmark solutions, and iterate toward production-quality implementations.

• Nice-to-have: Parameter-efficient fine-tuning (LoRA/QLoRA/PEFT), instruction tuning, dataset curation, or domain-specific model adaptation.
• Experience with graph databases or knowledge-graph augmented retrieval, GPU profiling/CUDA, or C/C++ and compiler concepts.
• Background or interest in digital logic, SystemVerilog, hardware verification, or EDA tools.
• Familiarity with LLM evaluation frameworks and experiment tracking platforms (MLflow, Weights & Biases).

Education Requirements

Not specified.

About the Company

Company: Siemens

Headquarters: Munich, Germany

Siemens EDA is a leading global provider of Electronic Design Automation (EDA) products and systems. Their innovative solutions enable companies to enhance the development of electronic products efficiently and effectively, keeping pace with the complex demands of technology and physics. Siemens is committed to delivering advanced workflow solutions that integrate both EDA and MCAD tools for multi-domain design and manufacturing in the semiconductor industry.