Principal Engineer, Efficient GenAI

AMD
San Jose, Seattle, Austin
Workplace: HybridFull timeUSD 210,000 - 360,000 annuallyFunction: Communications, PR & CommunityEducation: mastersSkills: ["Written communication","Verbal communication","Presentation skills","Coordination","Publishing externally"]

Build and scale efficient Generative AI training and inference for large foundation models as part of AMD’s AI Models and Applications team. Drive innovations across transformer architectures, distributed training parallelism, and inference optimizations like speculative decoding and KV-caching. Co-optimize end-to-end performance with software and hardware teams, integrate AMD-optimized model libraries using open-source frameworks, and publish results at external conferences.

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FursaFursa
AMD
AMD
2 days ago

Principal Engineer, Efficient GenAI

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Source: Company careers pageValidated by: Fursa AI
Last checked: 18 hours agoStatus: Live

Job Summary

Build and scale efficient Generative AI training and inference for large foundation models as part of AMD’s AI Models and Applications team. Drive innovations across transformer architectures, distributed training parallelism, and inference optimizations like speculative decoding and KV-caching. Co-optimize end-to-end performance with software and hardware teams, integrate AMD-optimized model libraries using open-source frameworks, and publish results at external conferences.
Location: San Jose, Seattle, Austin
Workplace: Hybrid
Employment Type: Full time
Job Function: Communications, PR & Community
Seniority: Mid level

Key Responsibilities

  • •Propose and apply techniques to improve both training and inference, including transformer architectures, training parallelism, speculative decoding, and KV-caching strategies.
  • •Implement efficient Generative AI model architectures for training and inference and demonstrate benefits on AMD platforms.
  • •Integrate AMD-optimized models and libraries with open-source frameworks and communities (e.g., PyTorch, JAX, vLLM, SGLang) 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, and publish work at major conferences.

Pay and Benefits

Salary: USD 210,000 - 360,000 annually

Key Requirements

  • •Deep hands-on experience with Generative AI applications such as LLMs, 3D World and Action Models, or image/video generation models.
  • •Experience training models at scale and developing efficient approaches for distributed training and inference on AMD devices.
  • •Strong technical expertise in Generative AI training and inference using deep learning frameworks such as PyTorch and JAX.
  • •Familiarity with efficient model architectures, optimized training, parallelism strategies, and low-precision training.
  • •PhD or master’s degree in computer science, Electrical Engineering, Mathematics, or a related field.
Experience:Generative aiDeep learning
Education:Master's in computer science, Electrical Engineering, Mathematics, or a related field
Skills:Written communicationVerbal communicationPresentation skillsCoordinationPublishing externally
Languages:En-us
Tech Stack:PyTorchJAXVLLMSGLangMuJoCoTransformer architecturesSpeculative decodingKV-cachingDistributed trainingAgentic workflows

Company Brief

AMD
Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1969
Glassdoor
Glassdoor: 3.9
WebsiteLinkedIn