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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Research Engineer, AI for Chip Design in Bellevue - **Company:** Energy Jobline - **Location:** Bellevue, WA, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Systems Engineering, C++ (Programming Language), Profiling, Nvidia CUDA, Computer Programming, Databases, Computer Engineering, Software Debugging, Microprocessors, Electronic Design Automation, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Software Engineering, Static Timing Analysis, SystemVerilog, Tcl (Programming Language), Verilog, Reinforcement Learning, Graphics Processing Unit (GPU), High Performance Computing, Pytorch, Large Language Models, Multi-Agent Systems, Parallel Computation, Information Technology, Codebase, Formal Methods, Virtual Agents, Physical Design - **Published:** August 8, 2026 - **Apply:** https://www.energyjobline.com/job/research-engineer-ai-chip-design-bellevue-31391059 ## About the Role * PhD or master's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent practical experience. * Strong programming skills in Python and proficiency in at least one systems such as C++ or Rust. * Experience with machine learning frameworks such as PyTorch or JAX. * Demonstrated research or engineering experience in one or more of the following: * Electronic Design Automation * Semiconductor design or verification * Agentic AI or large models * GPU-accelerated or parallel algorithms * Reinforcement learning * Combinatorial optimization * Program synthesis or code * Formal methods * Machine learning for engineering or scientific applications * Ability to take an ambiguous technical problem from initial formulation through experimentation, implementation, and evaluation. * Strong analytical, software engineering, optimization, and debugging skills. * High ownership, intellectual curiosity, and willingness to work across research and product boundaries. * Clear written and verbal communication skills. Particularly Valuable Experience * Publications in leading EDA, AI, machine learning, systems, high-performance computing, or computer architecture venues. * Experience developing new EDA algorithms, optimization engines, design representations, or domain-specific tools. * Experience developing GPU-accelerated algorithms using CUDA, Triton, or related parallel-computing technologies. * Experience profiling and optimizing computational workloads across CPUs and GPUs. * Experience designing tools or environments for use by autonomous agents. * Experience with simulation, verification, synthesis, timing analysis, physical design, analog design, or layout. * Experience building agents that interact with tools, codebases, databases, or external environments. * Experience with LLM training, post-training, fine-tuning, retrieval, tool use, or evaluation. * Familiarity with Verilog, SystemVerilog, assertions, SPICE, TCL, or semiconductor design flows. * Experience with commercial EDA tools or production chip-design environments. * Experience deploying AI systems in enterprise or security-sensitive environments. ## Description We are looking for an exceptional Research Engineer to develop new technologies at the intersection of artificial intelligence, agentic systems, GPU-accelerated computing, and Electronic Design Automation. You will identify important research problems, develop novel algorithms and agent- tools, build working prototypes, and help deploy them in real semiconductor design environments. Your work may span AI agents, large models, reinforcement learning, optimization, GPU-accelerated algorithms, verification, analog design, and other areas of chip design automation. This role is ideal for someone who combines strong research ability with exceptional implementation skills and wants to see their ideas used in production-not remain only in papers or prototypes. What You'll Do * Develop new AI and agentic methods for semiconductor design and verification. * Build novel agent- tools and algorithms designed specifically for autonomous engineering workflows, rather than adapting interfaces built primarily for human users. * Develop GPU-accelerated algorithms for computationally intensive design, analysis, search, simulation, and optimization problems. * Create tools that expose design state, constraints, actions, feedback, and optimization objectives in forms that agents can reason over and use effectively. * Build agents that can understand engineering objectives, use EDA tools, execute multi-step workflows, analyze results, recover from failures, and improve over time. * Research and implement techniques involving large models, reinforcement learning, parallel algorithms, search, optimization, program synthesis, and machine learning for engineering systems. * Develop solutions for workflows such as functional verification, analog and custom design, RTL development, synthesis, timing analysis, and physical design. * Design rigorous evaluation methods for engineering agents, including problems where design data is private, sparse, or customer-specific. * Translate promising research ideas into reliable, scalable product capabilities. * Integrate AI systems with simulators, formal tools, design databases, commercial EDA tools, GPU computing platforms, and customer engineering infrastructure. * Work directly with semiconductor engineers to understand complex workflows and identify high-impact automation opportunities. * Collaborate with research, product, platform, and solutions teams across San Jose, Austin, and Taiwan. * Contribute to patents, publications, technical presentations, and the broader development of Agentic Design Automation. ## Related Videos - [Building the Nervous System of AI - Michael Kagan (NVIDIA)](https://www.wearedevelopers.com/videos/2133-building-the-nervous-system-of-ai-michael-kagan-nvidia) - [Getting to Know Your Legacy (System) with AI-Driven Software Archeology](https://www.wearedevelopers.com/videos/1437-getting-to-know-your-legacy-system-with-ai-driven-software-archeology) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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