Santa Clara, United States 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 and co-op, 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: San Jose, CA or Santa Clara,CA
- Onsite/Hybrid: This role requires the student to work full time (40 hours a week), in either a hybrid or onsite work structure throughout the duration of the co-op/intern term
Duration:
- Spring/Summer Co-op: January 25, 2027 - August 13, 2027
- Summer Internship:
- Semester Students: May 24, 2027 - August 13, 2027
- Quarter Students: June 21, 2027 - September 10, 2027
- Summer/Fall Co-op:
- Semester Students: May 24, 2027 - December 10, 2027
- Quarter Students: June 21, 2027 - December 10, 2027
WHAT YOU WILL BE DOING:
We are seeking a motivated PhD intern to join our research team working at the intersection of High-Performance Computing (HPC) and Artificial Intelligence (AI). In this role, you will contribute to cutting-edge projects aimed at optimizing AI workloads for large-scale computing environments, developing novel algorithms, or exploring the integration of AI techniques to enhance HPC applications.
- Build, run, and analyze performance of benchmarks and application on GPU accelerated platforms.
- Assess the capabilities of development tools and runtime environment in terms of capabilities, performance, and usability.
- Explore the benefits of different code optimization techniques
Example projects include:
- Optimize communication patterns for HPC applications
- Investigate how GPU development tools can be adapted to future AMD GPUs
- Identify and measure performance capabilities across GPU families.
- Agents “ranger” through Jira/Atlassian to harvest reproducers.
- Use LLM workflows (maybe eventually agents) and existing Atlassian/Jira/Internal AMD AI available tools to incorporate existing bug reproducers
- Perform a thorough study porting simple synthetic workloads and maybe proxy apps to adaptiveCPP (SYCL) and measuring performance.
WHO WE ARE LOOKING FOR:
- Currently enrolled in a PhD program in Computer Science, Computational Science, Electrical/Computer Engineering, Applied Mathematics, or a related field.
- Strong background in parallel computing, distributed systems, or AI/ML frameworks.
- Proficiency in programming languages such as Python, C/C++, Fortrans or ROCm/CUDA.
- Experience with at least one deep learning framework (e.g., PyTorch, TensorFlow, JAX).
- Familiarity with MPI, OpenMP, or GPU programming.
- Solid understanding of numerical methods, optimization, or scientific computing.
- Experience with performance analysis, hot-spot identification
- Experience developing GPU kernels, analyzing and quantifying benefits of GPU offloading.
Note: By submitting your application, you are indicating your interest in AMD intern positions. We are recruiting for multiple positions, and if your experience aligns with any of our intern opportunities, a recruiter will contact you.
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 and co-op, 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: San Jose, CA or Santa Clara,CA
- Onsite/Hybrid: This role requires the student to work full time (40 hours a week), in either a hybrid or onsite work structure throughout the duration of the co-op/intern term
Duration:
- Spring/Summer Co-op: January 25, 2027 - August 13, 2027
- Summer Internship:
- Semester Students: May 24, 2027 - August 13, 2027
- Quarter Students: June 21, 2027 - September 10, 2027
- Summer/Fall Co-op:
- Semester Students: May 24, 2027 - December 10, 2027
- Quarter Students: June 21, 2027 - December 10, 2027
WHAT YOU WILL BE DOING:
We are seeking a motivated PhD intern to join our research team working at the intersection of High-Performance Computing (HPC) and Artificial Intelligence (AI). In this role, you will contribute to cutting-edge projects aimed at optimizing AI workloads for large-scale computing environments, developing novel algorithms, or exploring the integration of AI techniques to enhance HPC applications.
- Build, run, and analyze performance of benchmarks and application on GPU accelerated platforms.
- Assess the capabilities of development tools and runtime environment in terms of capabilities, performance, and usability.
- Explore the benefits of different code optimization techniques
Example projects include:
- Optimize communication patterns for HPC applications
- Investigate how GPU development tools can be adapted to future AMD GPUs
- Identify and measure performance capabilities across GPU families.
- Agents “ranger” through Jira/Atlassian to harvest reproducers.
- Use LLM workflows (maybe eventually agents) and existing Atlassian/Jira/Internal AMD AI available tools to incorporate existing bug reproducers
- Perform a thorough study porting simple synthetic workloads and maybe proxy apps to adaptiveCPP (SYCL) and measuring performance.
WHO WE ARE LOOKING FOR:
- Currently enrolled in a PhD program in Computer Science, Computational Science, Electrical/Computer Engineering, Applied Mathematics, or a related field.
- Strong background in parallel computing, distributed systems, or AI/ML frameworks.
- Proficiency in programming languages such as Python, C/C++, Fortrans or ROCm/CUDA.
- Experience with at least one deep learning framework (e.g., PyTorch, TensorFlow, JAX).
- Familiarity with MPI, OpenMP, or GPU programming.
- Solid understanding of numerical methods, optimization, or scientific computing.
- Experience with performance analysis, hot-spot identification
- Experience developing GPU kernels, analyzing and quantifying benefits of GPU offloading.
Note: By submitting your application, you are indicating your interest in AMD intern positions. We are recruiting for multiple positions, and if your experience aligns with any of our intern opportunities, a recruiter will contact you.
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