Role overview
About this role
ADVANCE YOUR CAREER. ADVANCE THE WORLD.
At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future.
Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.
As an AMD intern, you’ll be placed at the epicenter of the AI ecosystem, working alongside experts and industry pioneers. You’ll do important work, learn new skills, expand your network, and gain real-world experience on projects that impact millions of end-users worldwide. Whether you’re an undergrad or a PhD student, your contributions matter—and your experience here will be a launchpad for what comes next.
JOB DETAILS:
- Location: Orlando, Florida
- Onsite/Hybrid: This role requires the student to work full time onsite throughout the duration of the co-op/intern term.
- Duration: May 24, 2027 or June 21, 2027
AI Agentic Flow for GPU ASIC Design Intern/Co-op
We are seeking a highly motivated AI Agentic Flow for GPU ASIC Design Intern/Co-op to join our team. In this role, you will help develop and apply AI-driven agentic workflows that improve the efficiency, quality, and automation of GPU ASIC design and verification processes.
WHAT YOU WILL DO:
- We will involve you in developing AI agents that assist engineers with GPU ASIC design activities, including specification analysis, RTL development, verification planning, debug, and documentation generation.
- You will work with design, verification, and architecture teams to identify engineering workflows that can be enhanced through large language models (LLMs), retrieval systems, and autonomous AI agents.
- We will assign you projects to build, evaluate, and optimize agentic workflows that leverage engineering data sources such as design specifications, code repositories, simulation results, and technical documentation.
- Your responsibilities will include measuring AI agent effectiveness, analyzing workflow improvements, and helping create scalable solutions that improve engineering productivity and design quality.
WHAT YOU WILL LEARN:
- Gain hands-on experience applying AI and agentic systems to complex semiconductor engineering challenges.
- Learn modern GPU ASIC design and verification workflows used in advanced semiconductor development.
- Develop practical experience with large language models, AI agent frameworks, retrieval-augmented generation (RAG), automation pipelines, and engineering productivity tools.
- Work alongside experienced GPU architects, design engineers, verification engineers, and AI researchers on real-world engineering problems.
WHO WE ARE LOOKING FOR:
- Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Data Science, or a related technical field, with at least one year of coursework remaining after the internship/co-op.
- You are in your 3rd year, 4th year, or graduate-level studies with coursework in computer architecture, digital design, machine learning, artificial intelligence, or software engineering.
- Experience programming in Python and familiarity with software development practices, data structures, and algorithm design.
- Understanding of machine learning concepts, large language models, agentic AI systems, or AI application development through coursework, research, or personal projects.
- Familiarity with Linux environments, scripting, data analysis, or automation tools.
- Exposure to digital logic design, computer architecture, RTL development, hardware verification, or semiconductor design concepts.
PREFERRED QUALIFICATIONS:
- Experience building AI applications using LLMs, prompt engineering, RAG systems, vector databases, MCPs, or agent frameworks.
- Experience with Verilog, SystemVerilog, RTL design, simulation, verification, or hardware development projects.
- Knowledge of GPU architecture, parallel computing, hardware acceleration, or AI accelerator design.
- Experience analyzing large datasets, creating engineering automation solutions, or developing workflow orchestration tools.
- Participation in research projects, hackathons, open-source initiatives, or academic projects involving AI, semiconductor design, or hardware/software co-design
This role is not eligible for visa sponsorship.
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.
Qualifications
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.
Responsibilities
As an AMD intern, you’ll be placed at the epicenter of the AI ecosystem, working alongside experts and industry pioneers. You’ll do important work, learn new skills, expand your network, and gain real-world experience on projects that impact millions of end-users worldwide. Whether you’re an undergrad or a PhD student, your contributions matter—and your experience here will be a launchpad for what comes next.
JOB DETAILS:
- Location: Orlando, Florida
- Onsite/Hybrid: This role requires the student to work full time onsite throughout the duration of the co-op/intern term.
- Duration: May 24, 2027 or June 21, 2027
AI Agentic Flow for GPU ASIC Design Intern/Co-op
We are seeking a highly motivated AI Agentic Flow for GPU ASIC Design Intern/Co-op to join our team. In this role, you will help develop and apply AI-driven agentic workflows that improve the efficiency, quality, and automation of GPU ASIC design and verification processes.
WHAT YOU WILL DO:
- We will involve you in developing AI agents that assist engineers with GPU ASIC design activities, including specification analysis, RTL development, verification planning, debug, and documentation generation.
- You will work with design, verification, and architecture teams to identify engineering workflows that can be enhanced through large language models (LLMs), retrieval systems, and autonomous AI agents.
- We will assign you projects to build, evaluate, and optimize agentic workflows that leverage engineering data sources such as design specifications, code repositories, simulation results, and technical documentation.
- Your responsibilities will include measuring AI agent effectiveness, analyzing workflow improvements, and helping create scalable solutions that improve engineering productivity and design quality.
WHAT YOU WILL LEARN:
- Gain hands-on experience applying AI and agentic systems to complex semiconductor engineering challenges.
- Learn modern GPU ASIC design and verification workflows used in advanced semiconductor development.
- Develop practical experience with large language models, AI agent frameworks, retrieval-augmented generation (RAG), automation pipelines, and engineering productivity tools.
- Work alongside experienced GPU architects, design engineers, verification engineers, and AI researchers on real-world engineering problems.
WHO WE ARE LOOKING FOR:
- Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Data Science, or a related technical field, with at least one year of coursework remaining after the internship/co-op.
- You are in your 3rd year, 4th year, or graduate-level studies with coursework in computer architecture, digital design, machine learning, artificial intelligence, or software engineering.
- Experience programming in Python and familiarity with software development practices, data structures, and algorithm design.
- Understanding of machine learning concepts, large language models, agentic AI systems, or AI application development through coursework, research, or personal projects.
- Familiarity with Linux environments, scripting, data analysis, or automation tools.
- Exposure to digital logic design, computer architecture, RTL development, hardware verification, or semiconductor design concepts.
PREFERRED QUALIFICATIONS:
- Experience building AI applications using LLMs, prompt engineering, RAG systems, vector databases, MCPs, or agent frameworks.
- Experience with Verilog, SystemVerilog, RTL design, simulation, verification, or hardware development projects.
- Knowledge of GPU architecture, parallel computing, hardware acceleration, or AI accelerator design.
- Experience analyzing large datasets, creating engineering automation solutions, or developing workflow orchestration tools.
- Participation in research projects, hackathons, open-source initiatives, or academic projects involving AI, semiconductor design, or hardware/software co-design