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_

MACHINE LEARNING ENGINEER 

THE ROLE:

We are looking for a Machine Learning Engineer to join our Models and Applications team. If you are excited by the challenge of distributed training of large models on a large number of GPUs, and if you are passionate about improving training efficiency while innovating and generating new ideas, then this role is for you.  You will be part of a world class team focused on addressing the challenge of training generative AI.

THE PERSON:

The ideal candidate should have experience with distributed training pipelines, be knowledgeable in distributed training algorithms (Data Parallel, Tensor Parallel, Pipeline Parallel, ZeRO), and be familiar with training large models.

KEY RESPONSIBILITIES:

• Train large models to convergence on AMD GPUs.
• Improve the end-to-end training pipeline performance.
• Optimize the distributed training pipeline and algorithm to scale out.
• Contribute your changes to open source.
• Stay up-to-date with the latest training algorithms.
• Influence the direction of AMD AI platform. 
• Collaborate across teams with various groups and stakeholders.

PREFERRED EXPERIENCE:

• Experience with ML frameworks such as PyTorch, JAX, or TensorFlow.
• Experience with distributed training and distributed training frameworks, such as DeepSpeed.
• Experience with LLMs or computer vision, especially large models, is a plus.
• Excellent Python programming skills, including debugging, profiling, and performance analysis.
• Experience with ML pipelines.
• Strong communication and problem-solving skills.

ACADEMIC CREDENTIALS:

• A Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

LOCATION:

San Jose, CA

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.

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.

MACHINE LEARNING ENGINEER 

THE ROLE:

We are looking for a Machine Learning Engineer to join our Models and Applications team. If you are excited by the challenge of distributed training of large models on a large number of GPUs, and if you are passionate about improving training efficiency while innovating and generating new ideas, then this role is for you.  You will be part of a world class team focused on addressing the challenge of training generative AI.

THE PERSON:

The ideal candidate should have experience with distributed training pipelines, be knowledgeable in distributed training algorithms (Data Parallel, Tensor Parallel, Pipeline Parallel, ZeRO), and be familiar with training large models.

KEY RESPONSIBILITIES:

• Train large models to convergence on AMD GPUs.
• Improve the end-to-end training pipeline performance.
• Optimize the distributed training pipeline and algorithm to scale out.
• Contribute your changes to open source.
• Stay up-to-date with the latest training algorithms.
• Influence the direction of AMD AI platform. 
• Collaborate across teams with various groups and stakeholders.

PREFERRED EXPERIENCE:

• Experience with ML frameworks such as PyTorch, JAX, or TensorFlow.
• Experience with distributed training and distributed training frameworks, such as DeepSpeed.
• Experience with LLMs or computer vision, especially large models, is a plus.
• Excellent Python programming skills, including debugging, profiling, and performance analysis.
• Experience with ML pipelines.
• Strong communication and problem-solving skills.

ACADEMIC CREDENTIALS:

• A Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

LOCATION:

San Jose, CA