Sr. AI/ML Engineer

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. 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. In this role, you will design and develop a robust, modular agentic ecosystem where specialized AI agents leverage advanced reasoning, retrieval-augmented generation (RAG), and structured tool execution to support complex IP development tasks. You will collaborate closely with IP and SoC teams to transform AI prototypes into reliable, enterprise-grade engineering solutions. THE PERSON: 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. This individual will build credibility quickly with hardware engineering teams by understanding the rigor required for silicon production and approaches challenges with a focus on making AI-driven workflows auditable, reliable, and production-ready. KEY 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 PREFERRED EXPERIENCE: • 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 ACADEMIC CREDENTIALS: Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering, or a related technical field LOCATION:  • Austin, TX (Primary) • Additional flexibility across AMD locations or hybrid arrangements as needed. This role is not eligible for visa sponsorship. #LI-MO2 #LI-Hybrid Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy. 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. In this role, you will design and develop a robust, modular agentic ecosystem where specialized AI agents leverage advanced reasoning, retrieval-augmented generation (RAG), and structured tool execution to support complex IP development tasks. You will collaborate closely with IP and SoC teams to transform AI prototypes into reliable, enterprise-grade engineering solutions. THE PERSON: 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. This individual will build credibility quickly with hardware engineering teams by understanding the rigor required for silicon production and approaches challenges with a focus on making AI-driven workflows auditable, reliable, and production-ready. KEY 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 PREFERRED EXPERIENCE: • 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 ACADEMIC CREDENTIALS: Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering, or a related technical field LOCATION:  • Austin, TX (Primary) • Additional flexibility across AMD locations or hybrid arrangements as needed. This role is not eligible for visa sponsorship. #LI-MO2 #LI-Hybrid Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.