Staff AI Models GPU Deployment Software Engineer at Advanced Micro Devices, Inc

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

30 Apr, 26

Salary

0.0

Posted On

30 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

C++, Python, AI Development, Linux, GPU Computing, HIP, CUDA, OpenCL, Natural Language Processing, Vision, Audio, Recommendation Systems, Debugging, Performance Analysis, Test Design

Industry

Semiconductor Manufacturing

Description

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. THE ROLE: AMD is looking for a software engineer who is passionate about expanding AI models on AMD GPUs, and improving the performance of key applications and benchmarks. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology. THE PERSON: Strong technical and analytical skills in C++/Python AI 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: Enable and optimize key AI models (LLM, Vision, MultiModal, etc.) on AMD GPUs Optimize AI frameworks like PyTorch, TensorFlow, etc. on AMD GPUs in upstream open-source repositories Collaborate and interact with internal GPU library teams to analyze and optimize training and inference for AI Work with open-source framework maintainers to understand their requirements – and have your code changes integrated upstream Optimize GPU kernels, understand and drive AI operator performance (GEMM, Attention, etc.) with specialized teams Work in a distributed computing setting to optimize for both scale-up (multi-GPU) and scale-out (multi-node) systems Apply your knowledge of software engineering best practices PREFERRED EXPERIENCE: Knowledge of GPU computing (HIP, CUDA, OpenCL) AI model experience or knowledge - Natural Language Processing, Vision, Audio, Recommendation systems Excellent C/C++/Python programming and software design skills, including debugging, performance analysis, and test design. Experiences to run workloads on large scale heterogeneous cluster is a plus Experiences to optimize GPU kernels for performance is a plus ACADEMIC CREDENTIALS: Masters or PhD or equivalent experience in Computer Science, Computer Engineering, or related field #LI-NR1 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

The role involves enabling and optimizing key AI models on AMD GPUs and collaborating with internal GPU library teams to enhance training and inference for AI. The engineer will also work with open-source framework maintainers to integrate code changes upstream.