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Principal Engineer, Efficient GenAI

  • Markham, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
Posted

Original job 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.  

Responsibilities

THE ROLE:

The AI Models and Applications team at AMD is looking for a specialized Principal Engineer who is passionate about enabling innovative and efficient Generative AI training and inference at scale. You will be part of a core team of incredibly talented specialists and work on scaling training and inference for the latest Generative AI models.

THE PERSON:

You have a deep technical understanding and hands-on experience with the latest Generative AI applications in at least one of the following areas: large language models (LLMs), 3D World and Action Models, or image/video generation models. You have experience training models at scale and are passionate about developing efficient approaches to enable distributed training and inference on AMD devices.

Why Join Us?

  • Exciting Opportunities: As a senior member of the team, you will be at the forefront of innovation, working with the latest Generative AI models and algorithms. You will have the opportunity to shape the future of AI model training and inference optimization across a variety of applications.
  • Talented Team: Join a team of highly skilled industry specialists who are passionate about pushing the boundaries of AI. Collaborate with like-minded professionals and learn from the best in the field.
  • Cutting-Edge Technology: Work with state-of-the-art Generative AI algorithms and software, enabling you to stay ahead of the curve and drive advancements in AI model training at scale and deployment.
  • Impactful Work: Your contributions will directly influence how cutting-edge Generative AI models across the industry are efficiently trained at scale, as well as how inference solutions are deployed to serve millions of customers, making a significant difference across various industries and applications.

KEY RESPONSIBILITIES:

  • Propose and apply innovative techniques to support both training and inference, including innovative transformer architectures, parallelism strategies for training on large clusters, inference optimization techniques such as speculative decoding, and optimal KV-caching strategies.
  • Implement novel, efficient architectures for Generative AI models for training and inference and showcase the benefits on AMD platforms.
  • Work with open-source frameworks and communities (e.g., PyTorch, JAX, vLLM, SGLang) to integrate AMD-optimized models and libraries and publish training recipes.
  • Collaborate with software and hardware teams to co-optimize end-to-end performance on current and future AMD solutions.
  • Increase adoption of agentic workflows for optimizing and deploying Generative AI applications at scale on AMD platforms.
  • Publish and promote your work at external venues, including major conferences.
  • Collaborate with researchers within AMD and across industry and academia to promote innovation on AMD platforms.

PREFERRED EXPERIENCE:

  • Strong technical expertise in Generative AI model training and inference, with familiarity working with deep learning frameworks such as PyTorch, JAX, vLLM, SGLang, and MuJoCo.
  • Strong technical expertise in algorithmic innovation for efficient Generative AI applications across both training and inference.
  • Expertise and publications in one or more of the following preferred areas: efficient model architectures, optimized training, innovative parallelism strategies, or low-precision training.
  • Additional plus if publications have been presented at conferences such as NeurIPS, CVPR, ECCV, ICCV, ICML, or ICLR.
  • Experience productizing Generative AI models and training foundation models at scale.
  • Excellent written, verbal, and presentation skills, with the ability to coordinate effectively both internally and externally.
  • Several years of experience in AI, deep learning, and related software development.

ACADEMIC CREDENTIALS:

PhD or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field.

LOCATION:

Markham, Ontario, Canada

Qualifications

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.

More about this job

Responsibilities

The Principal Engineer at AMD will design and apply efficient techniques for training and running Generative AI models at scale. They will also work with software and hardware teams, open-source communities and researchers to improve performance on AMD products.

Requirements

Candidates need deep hands-on experience with large language models, 3D world models or image/video generation, and experience training models at scale. A PhD or Master's in a related field and several years of AI and deep learning experience are preferred.

Skills

  • PyTorch
  • JAX
  • vLLM
  • SGLang
  • MuJoCo
  • Distributed training
  • Parallelism strategies
  • Speculative decoding
  • KV caching
  • Transformer architectures
  • Low-precision training
  • Inference optimization
  • Model training at scale
  • Deep learning
  • Generative AI
  • Large language models
  • Image and video generation models
  • Software development
  • Research publication
  • Technical presentation
  • Cross-team collaboration

Benefits

  • AMD benefits

Categories

  • Technology
  • Software
  • Data & Analytics
  • Engineering
  • Science & Research

Keywords

  • Generative AI
  • large language models
  • LLM inference
  • LLM training
  • PyTorch
  • JAX
  • vLLM
  • SGLang
  • MuJoCo
  • distributed training
  • model parallelism
  • speculative decoding
  • KV caching
  • low-precision training
  • efficient model architectures
  • AMD
  • deep learning
  • machine learning engineer
  • AI engineer
  • principal engineer

Seniority

Senior

Tools

  • PyTorch
  • JAX
  • vLLM
  • SGLang
  • MuJoCo

Languages

  • English

Fields of study

  • Computer Science
  • Electrical Engineering
  • Mathematics

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