Sr. Machine Learning/ HPC Architect Full-time

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_

THE ROLE:

AMD’s Machine Learning (ML) /High Performance Computing (HPC) Architecture team is passionate about developing next-generation GPU solutions. As a Sr. Machine Learning/ HPC Architect, you will collaborate with a strong architecture and design team on developing next generation products for data centers and super-computers.

THE PERSON:

You will engage in architecture exploration, modeling, and analysis of ML/HPC workloads. Through your experiments and analysis, you will provide valuable insight into new and emerging hardware and software technologies.

• Communicate and collaborate with a network of experienced architects and designers around the world
• Work with architects to propose innovative solutions that can be implemented in HW and validated by developing various models/simulators
• Collect/summarize data or simulation results for consumption by architects and design teams
• Identify complex technical problems, break them down, summarize possible solutions
• Excellent analytical and problem-solving skills, along with attention to detail
• Effective team player who focuses on collaboration, team building, mentoring, and furthering team success.
• Strong communication, time management, and presentation skills

KEY RESPONSIBILITIES:

• Coding proficiency in Python
• Experience with performance analysis and modelling for computer architectures
• Experience with Machine Learning models and understanding of core concepts in neural networks
• Knowledge of ML networks, frameworks, tools and environments: Tensorflow, Pytorch, etc
• Experience with development/optimization of low level kernels
• Knowledge of HW/RTL/ SystemC

PREFERRED EXPERIENCE:

• Experience with Machine Learning concepts and Computer Architecture
• Strong knowledge of Machine Learning GPU Architecture
• Strong proficiency in multiple coding/scripting languages (C/C++)
• Experience with Graphics/Compute APIs (CUDA/OpenCL/Vulkan etc.)
• Knowledge of OS/device drivers is a plus

ACADEMIC CREDENTIALS:

• Undergrad required. Master or PhD degree in Electrical Engineering, Computer architecture, or Computer Science preferred

#LI-BM1

#LI-Hybrid

#LI-Hybrid

At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

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.