Senior AI GPU Compiler Engineer
Senior AI GPU Compiler Engineer

Senior AI GPU Compiler Engineer

Cambridge Full-Time 48000 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join us to optimise AI frameworks and develop GPU kernels for cutting-edge AMD technology.
  • Company: AMD is a leader in tech innovation, transforming lives with powerful computing solutions.
  • Benefits: Enjoy competitive perks, inclusive culture, and opportunities for remote work.
  • Why this job: Be part of a collaborative team pushing the boundaries of AI and deep learning.
  • Qualifications: Bachelor's/Master's in Computer Science/Engineering and 3+ years in GPU optimisation required.
  • Other info: Diverse candidates are encouraged to apply; we value unique perspectives.

The predicted salary is between 48000 - 72000 £ per year.

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.

Sr. SOFTWARE DEVELOPMENT ENGINEER

THE ROLE:

AI Software development engineer on teams building and optimizing Deep Learning applications and AI frameworks for AMD GPU compute platforms. Work as part of an AMD development team and open-source community to analyze, develop, test and deploy improvements to make AMD the best platform for machine learning applications.

THE PERSON:

Strong technical and analytical skills in C++ development in a Linux environment. Ability to work as part of a team, while also being able to work independently, define goals and scope and lead your own development effort.

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: Proficient 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: Proficient 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: Proficient skills in Python and C++, with experience in debugging, performance tuning, and test design to ensure high-quality, maintainable software solutions.
  • High-Performance Computing: Proficient experience in running large-scale workloads on heterogeneous compute clusters, optimizing for efficiency and scalability.
  • Compiler Optimization: Solid 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/or 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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Senior AI GPU Compiler Engineer employer: AMD

At AMD, we are committed to fostering a culture of innovation and collaboration, making us an exceptional employer for those passionate about technology and AI. Our inclusive work environment encourages personal and professional growth, offering opportunities to work on cutting-edge projects that shape the future of computing. Located in a vibrant tech hub, employees benefit from a dynamic atmosphere that promotes creativity and teamwork, alongside competitive benefits that support a healthy work-life balance.
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Contact Detail:

AMD Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior AI GPU Compiler Engineer

✨Tip Number 1

Familiarise yourself with AMD's technology and products. Understanding their GPU architectures, like GCN and RDNA, will not only help you in interviews but also show your genuine interest in the company and its mission.

✨Tip Number 2

Engage with the open-source community related to AMD GPUs. Contributing to projects or discussions on platforms like GitHub can demonstrate your skills and commitment to optimising deep learning frameworks, which is a key responsibility of the role.

✨Tip Number 3

Network with current AMD employees or professionals in the field. Attend industry conferences or webinars focused on AI and GPU technologies to make connections that could provide insights into the company culture and the specifics of the role.

✨Tip Number 4

Prepare for technical interviews by brushing up on your C++ and Python skills, especially in the context of GPU kernel development. Practising coding challenges that focus on performance optimisation will give you an edge during the interview process.

We think you need these skills to ace Senior AI GPU Compiler Engineer

C++ Development
Linux Environment Proficiency
Deep Learning Frameworks (TensorFlow, PyTorch)
GPU Kernel Development
Performance Optimization
Machine Learning Model Design
Collaboration with Open-Source Communities
Distributed Computing Environments
Compiler Technologies (LLVM, ROCm)
High-Performance Computing
Debugging and Performance Tuning
Software Engineering Best Practices
Knowledge of AMD Architectures (GCN, RDNA)
Python Programming
Test Design and Implementation

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience with C++ development, GPU optimization, and deep learning frameworks like TensorFlow and PyTorch. Use specific examples to demonstrate your skills in these areas.

Craft a Strong Cover Letter: In your cover letter, express your passion for AI and how your background aligns with AMD's mission. Mention any relevant projects or experiences that showcase your ability to work independently and as part of a team.

Showcase Technical Skills: Clearly outline your technical skills related to GPU kernel development, compiler optimization, and high-performance computing. Include any relevant tools and technologies you have worked with, such as HIP, CUDA, and LLVM.

Highlight Collaborative Experience: Since collaboration is key in this role, provide examples of how you've successfully worked with teams or contributed to open-source projects. This will demonstrate your ability to engage with others and improve performance on AMD GPUs.

How to prepare for a job interview at AMD

✨Showcase Your Technical Skills

Be prepared to discuss your experience with C++ development in a Linux environment. Highlight specific projects where you've optimised GPU kernels or deep learning frameworks, as this will demonstrate your technical prowess and relevance to the role.

✨Understand AMD's Culture

Familiarise yourself with AMD's mission and values. During the interview, express how your personal values align with their focus on innovation, collaboration, and inclusivity. This will show that you're not just a fit for the role, but also for the company culture.

✨Prepare for Problem-Solving Questions

Expect to face technical challenges or case studies related to GPU optimisation and deep learning. Practice explaining your thought process clearly and logically, as this will showcase your analytical skills and ability to work through complex problems.

✨Engage with the Interviewers

Don't hesitate to ask questions about the team dynamics, ongoing projects, or the technologies they use. This shows your genuine interest in the position and helps you assess if the role is the right fit for you.

Senior AI GPU Compiler Engineer
AMD

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A
  • Senior AI GPU Compiler Engineer

    Cambridge
    Full-Time
    48000 - 72000 £ / year (est.)

    Application deadline: 2027-08-02

  • A

    AMD

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