Principal Software Development Engineer

Advanced Micro Devices; San Jose (CA); Hybrid; USD 130,000 - 180,000; Full time

Job summary

A leading company is seeking a Principal Software Development Engineer to join their Models and Applications team. The role focuses on improving training efficiency for generative AI and requires expertise in distributed training and machine learning frameworks. The ideal candidate will have strong Python skills and a Master's degree in a relevant field. This hybrid position is based in San Jose, CA.

Qualifications

• Experience with distributed training pipelines and algorithms.
• Familiarity with training large models.

Responsibilities

• Train large models to convergence on AMD GPUs.
• Optimize the distributed training pipeline and algorithm.
• Collaborate across teams with various groups and stakeholders.

Skills

Python

Communication

Problem-Solving

Education

Master's degree in Computer Science

Master's degree in Artificial Intelligence

Master's degree in Machine Learning

Tools

PyTorch

JAX

TensorFlow

DeepSpeed

Job description

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_

PRINCIPAL SOFTWARE DEVELOPMENT ENGINEER

• THE ROLE:

  We are looking for a Principal 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 (Hybrid)

#LI-MV1

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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.