Sr. AI/ML Engineer

About the role

The Role We are seeking a hands-on AI/ML developer to build, scale and deploy the next generation AI-assisted silicon design framework. This role sits at the intersection of production software engineering, AI orchestration, and hardware infrastructure, enabling acceleration of the specification-to-netlist lifecycle.

Responsibilities

• Design and deploy modular AI agent architectures capable of task decomposition, structured tool usage, and iterative code generation across the spec-to-RTL lifecycle
• Develop and optimize multi-step agent workflows, including prompt orchestration, context management, and state handling for complex engineering tasks
• Build and scale hybrid retrieval systems, including RAG pipelines and knowledge graphs, to ground AI agents in hardware specifications, protocols, and architectural data
• Develop closed-loop automation systems that enable AI agents to interpret and respond to compiler errors and EDA tool outputs (e.g., lint, simulation) for iterative design refinement
• Build and maintain secure, low-latency infrastructure to integrate LLMs with external tools using Model Context Protocol (MCP) and custom APIs
• Partner with IP and Subsystem teams to integrate AI-driven workflows into existing silicon development processes
• Establish evaluation frameworks and automated pipelines to validate AI-generated outputs for correctness, synthesis readiness, and power, performance, and area (PPA) targets

Requirements

The ideal candidate is a pragmatic AI/ML engineer with a strong systems mindset who prioritizes robustness, predictability, and scalability over experimental AI demonstrations. They are detail-oriented and deeply focused on deterministic guardrails, error handling, and performance optimization.

Qualifications

• Experience developing production-grade AI/LLM applications and agent-based systems
• Hands-on experience with orchestration frameworks such as LangChain, AutoGen, CrewAI, or similar graph-based agent architectures
• Strong understanding of API development and integrating LLMs with external systems and tools
• Familiarity with Model Context Protocol (MCP) or similar tool-calling frameworks
• Foundational understanding of silicon IP design and verification workflows, including exposure to Verilog/SystemVerilog or digital design concepts
• Familiarity with EDA tools (e.g., Synopsys, Cadence, Siemens) and Linux-based development environments
• Strong software engineering skills in Python, C++, Go, or similar languages, with experience building scalable, secure, and modular systems

Skills

Academic Credentials Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering, or a related technical field

Benefits

AMD benefits at a glance.

Pay

N/A

Schedule

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Benefits

AMD benefits at a glance.