AMDML Kernel Software Development Engineer
任职要求
The ideal candidate possesses an innovative and problem-solving mindset, has a keen eye for Software engineering development, and is diligent and passionate about Technology. KEY RESPONSIBILITIES: Develop and optimize ML kernels with focus on performance and scalability. Collaborate with cross-functional teams to understand requi…
工作职责
THE ROLE: We are seeking a talented and motivated New College Graduate to join our ROCm Core team. You will be responsible for enhancing and optimizing ML kernels to improve performance and efficiency. This is an exciting opportunity to work with cutting-edge technologies and contribute to innovative ML solutions.
An exciting internship opportunity to make an immediate contribution to AMD's next generation of technology innovations awaits you! We have a multifaceted, high-energy work environment filled with a diverse group of employees, and we provide outstanding opportunities for developing your career. During your internship, our programs provide the opportunity to collaborate with AMD leaders, receive one-on-one mentorship, attend amazing networking events, and much more. Being part of AMD means receiving hands-on experience that will give you a competitive edge. Together We Advance your career! JOB DETAILS: Location: Shanghai, China Onsite/Hybrid: This role require the student to work at least 3 days/week, either in a hybrid (minimum 3 Days in Office) or onsite work structure throughout the duration of the co-op/intern term. Duration: Jan - June 2026 WHAT YOU WILL BE DOING: We are seeking a highly motivated Machine Learning (ML)/Artificial Intelligence (AI) intern/co-op to join our team and contribute to the development of next-generation product differentiation features alongside expert ML/AI engineers. In this role, you will: Gain hands-on experience with cutting-edge technologies in ML, AI, and High-Performance Computing. Learn to analyze and optimize GPU Kernel to maximize performance for specific AI operations. Contribute to projects such as: Researching, developing, and deploying machine learning and computer vision solutions for AMD's current and future products. Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs. Design and optimize deep learning models specifically for AMD GPU performance. Assisting AI software teams with roadmap planning, collateral development, and customer engagements. Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream. Apply sound engineering principles to ensure robust, maintainable solutions.
Introduction to the job 运用机器学习技术开发和优化算法,从而提高芯片制造的效率和质量 Role and responsibilities 运用机器学习技术开发和优化算法,从而提高芯片制造的效率和质量
An exciting internship opportunity to make an immediate contribution to AMD's next generation of technology innovations awaits you! We have a multifaceted, high-energy work environment filled with a diverse group of employees, and we provide outstanding opportunities for developing your career. During your internship, our programs provide the opportunity to collaborate with AMD leaders, receive one-on-one mentorship, attend amazing networking events, and much more. Being part of AMD means receiving hands-on experience that will give you a competitive edge. Together We Advance your career! JOB DETAILS: Location: Shanghai Onsite/Hybrid: This role requires the student to work full time (40 hours a week), either in a hybrid or onsite work structure throughout the duration of the co-op/intern term. Duration: January 1, 2026 - June 30, 2026 WHAT YOU WILL BE DOING: We are seeking highly motivated AI/ML Engineering Intern to join our AMD Research team. In this role: You will develop machine learning models to optimize GPU power/performance tradeoffs using real-world silicon data. We will train you to deploy models via MLOps pipelines for AMD’s internal tools. Your responsibility will include analyzing hardware telemetry data (power, thermal, clocks) to identify efficiency bottlenecks. You will collaborate with hardware engineers to validate models on next-gen AMD GPUs. Learning Outcomes: Master GPU-accelerated ML workflows. Gain hands-on experience with industrial-scale MLOps.