Synopsys

We Are: 

At Synopsys, we drive the innovations that shape how next-generation chips are made. Our TCAD team builds simulation engines that power semiconductor process R&D at leading manufacturers worldwide. We drive performance breakthroughs by building agentic AI/ML systems that continuously learn to generate multi-physics models used in semiconductor manufacturing. Join us and see your work adopted by top tier foundries and research labs globally—real-world impact at scale. 

You Are: 

A skilled and motivated software engineer who wants to build innovative products that directly impact real-world chip fabrication and accelerate next generation chip technology. You thrive in a global, collaborative environment and enjoy working closely with colleagues across multidisciplinary domains. You communicate clearly, value diverse perspectives, and contribute actively to turning complex ideas into solid outcomes. You care deeply about engineering quality, reproducibility, and long-term sustainability. 

What You’ll Be Doing:  

• You will design and operate agent‑based AI/ML systems that continuously improve how multi‑physics models are generated, evaluated, and optimized. The focus is not on isolated model inference, but on closed‑loop systems that connect AI‑driven generation with execution, validation, and systematic learning under real engineering constraints. 
• Integrate simulation and execution backends through secure, well-typed tool interfaces, enabling reliable and automated model execution on HPC and containerized runtimes. 
• Establish closed feedback loops that collect logs, metrics, numerical data, and visual outputs for evaluation and iterative improvement. 
• Normalize and structure heterogeneous outputs to support downstream analysis and learning across iterations. 
• Work at the intersection of AI/ML, explainability, numerical methods, and high‑performance computing. 
• Collaborate closely with physics, TCAD, and software experts to translate ambiguous physical objectives into robust, automated modeling workflows. 

What You’ll Need: 

• PhD or MS in Computer Science, Engineering or Applied Mathematics with 3+ years of experience developing large, complex engineering applications 
• Strong programming skills in Python and modern C++, including work in performance‑critical or scientific codebases 
• Ability to design, fine‑tune, and deploy domain-adapted LLMs in air‑gapped or on‑prem environments 
• Ability to translate ambiguous goals into robust AI architectures that work under real constraints 
• Deep understanding of agentic systems: planning, tool use, memory, multi‑agent coordination, self‑improvement loops 
• Hands‑on experience with RAG architectures (data ingestion, indexing, retrieval, evaluation) 
• Proven capability to design and implement MCP servers, exposing secure, well‑typed, auditable AI‑tool interfaces 
• Good interpersonal and communication skills. Good English language skills are required. 

 
Nice to have: 

• Experience with scientific or engineering simulation and applications. 
• Experience with platforms and components such as NVIDIA Omniverse, container runtime, NVIDIA PhysicsNeMo, etc. 
• Understanding of multi-modal LLM and multi-agent architectures. 

#TPG 

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.