At a Glance
- Tasks: Join us to optimise and develop deep learning frameworks for AMD GPUs.
- Company: AMD is a leader in technology, transforming lives with innovative computing solutions.
- Benefits: Enjoy competitive benefits, including flexible work options and a collaborative culture.
- Why this job: Be part of a team pushing the limits of innovation in AI and gaming.
- Qualifications: Strong C++ skills and experience in GPU kernel development are essential.
- Other info: Open to diverse applicants; we value inclusion and unique perspectives.
The predicted salary is between 36000 - 60000 £ per year.
SOFTWARE DEVELOPMENT ENGINEER– GPU KERNEL DEVELOPMENT
SOFTWARE DEVELOPMENT ENGINEER– GPU KERNEL DEVELOPMENT
WHAT YOU DO AT AMD CHANGES EVERYTHING
We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.
WHAT YOU DO AT AMD CHANGES EVERYTHING
We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.
AMD together we advance_
GPU KERNEL DEVELOPMENT
THE ROLE:
As a core member of the team, you will play a pivotal role in optimizing and developing deep learning frameworks for AMD GPUs. Your experience will be critical in enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems. You will engage with both internal GPU library teams and open-source maintainers to ensure seamless integration of optimizations, utilizing cutting-edge compiler technologies and advanced engineering principles to drive continuous improvement.
THE PERSON:
Skilled engineer with strong technical and analytical expertise in C++ development within Linux environments. The ideal candidate will thrive in both collaborative team settings and independent work, with the ability to define goals, manage development efforts, and deliver high-quality solutions. Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices are essential.
KEY RESPONSIBILITIES:
- Optimize Deep Learning Frameworks: Enhance and optimize frameworks like TensorFlow and PyTorch for AMD GPUs in open-source repositories.
- Develop GPU Kernels: Create and optimize GPU kernels to maximize performance for specific AI operations.
- Develop & Optimize Models: Design and optimize deep learning models specifically for AMD GPU performance.
- Collaborate with GPU Library Teams: Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs.
- Collaborate with Open-Source Maintainers: Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream.
- Work in Distributed Computing Environments: Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems.
- Utilize Cutting-Edge Compiler Tech: Leverage advanced compiler technologies to improve deep learning performance.
- Optimize Deep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers.
- Software Engineering Best Practices: Apply sound engineering principles to ensure robust, maintainable solutions.
PREFERRED EXPERIENCE:
- GPU Kernel Development & Optimization: Experienced in designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM). Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming to maximize performance for AI operations, leveraging tools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance.
- Deep Learning Integration: Experienced in integrating optimized GPU performance into machine learning frameworks (e.g., TensorFlow, PyTorch) to accelerate model training and inference, with a focus on scaling and throughput.
- Software Engineering: Skilled in Python and C++, with experience in debugging, performance tuning, and test design to ensure high-quality, maintainable software solutions.
- High-Performance Computing: Solid experienced in running large-scale workloads on heterogeneous compute clusters, optimizing for efficiency and scalability.
- Compiler Optimization: Foundational understanding of compiler theory and tools like LLVM and ROCm for kernel and system performance optimization.
ACADEMIC CREDENTIALS:
- Bachelor’s and/or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
- 3+ years of professional experience in technical software development, with a focus on GPU optimization, performance engineering, and framework development.
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.
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SOFTWARE DEVELOPMENT ENGINEER– GPU KERNEL DEVELOPMENT employer: AMD
Contact Detail:
AMD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land SOFTWARE DEVELOPMENT ENGINEER– GPU KERNEL DEVELOPMENT
✨Tip Number 1
Familiarise yourself with AMD's GPU architectures, such as GCN and RDNA. Understanding these will not only help you in interviews but also demonstrate your genuine interest in the role and the company.
✨Tip Number 2
Engage with open-source communities related to deep learning frameworks like TensorFlow and PyTorch. Contributing to these projects can showcase your skills and commitment to optimising GPU performance.
✨Tip Number 3
Brush up on your knowledge of compiler technologies, especially LLVM and ROCm. Being able to discuss how these tools can enhance performance during your interview will set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your experience with multi-GPU and multi-node systems. Be ready to share specific examples of how you've optimised performance in these environments, as this is a key aspect of the role.
We think you need these skills to ace SOFTWARE DEVELOPMENT ENGINEER– GPU KERNEL DEVELOPMENT
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in C++ development, GPU kernel optimisation, and deep learning frameworks. Use specific examples that demonstrate your skills and achievements relevant to the role.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for AMD's mission and culture. Discuss how your background in software engineering and GPU optimisation aligns with their goals, and mention any collaborative projects you've worked on.
Showcase Relevant Projects: Include details of any projects where you have optimised deep learning models or developed GPU kernels. Highlight your problem-solving skills and any tools or technologies you used, such as HIP or CUDA.
Prepare for Technical Questions: Anticipate technical questions related to GPU architecture, compiler optimisation, and performance tuning. Be ready to discuss your approach to solving complex problems and how you stay updated with industry trends.
How to prepare for a job interview at AMD
✨Showcase Your Technical Skills
Be prepared to discuss your experience with C++ development, particularly in Linux environments. Highlight specific projects where you've optimised GPU kernels or deep learning frameworks, and be ready to explain the technical challenges you faced and how you overcame them.
✨Demonstrate Problem-Solving Abilities
Expect to encounter technical questions that assess your problem-solving skills. Use the STAR method (Situation, Task, Action, Result) to structure your responses, showcasing how you approached complex issues in previous roles, especially related to GPU optimisation.
✨Familiarise Yourself with AMD's Culture
Research AMD's mission and values, focusing on their commitment to innovation and collaboration. Be ready to discuss how your personal values align with theirs and provide examples of how you've worked effectively in team settings or contributed to a collaborative environment.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with internal teams and open-source maintainers, prepare to discuss your experience in collaborative projects. Think of examples where you successfully integrated feedback from others or contributed to open-source initiatives, demonstrating your ability to work well with diverse perspectives.