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Emily Webber

Principal machine learning specialist solutions architect, AWS Trainium team, Amazon

Emily Webber is a principal machine learning specialist solutions architect on the AWS Trainium team within Annapurna Labs. In August 2026, Webber co-wrote Amazon Science's announcement of the AWS Trainium Frontier competition, in which teams build language models from scratch on Trainium under a fixed training budget, with a finalist event at NeurIPS 2026. Webber is the author of the 2023 Packt book Pretrain Vision and Large Language Models in Python, whose MIT-licensed companion repository walks through preparing, training, fine-tuning, evaluating and deploying foundation models on Amazon SageMaker.123

At a glance

Current role
Principal machine learning specialist solutions architect, AWS Trainium team
Company
Amazon
Sector
Company
Work listed
2
Sources cited
3
Profile reviewed

Career

Emily Webber is a principal machine learning specialist solutions architect on the AWS Trainium team within Annapurna Labs, and Webber's GitHub profile describes the role as principal solutions architect at Annapurna ML. The author note in Webber's 2023 book describes earlier work at AWS on distributed training for large language and vision models, mentoring ML solutions architects, and advising the Amazon SageMaker product and engineering teams.123

The same note records a keynote at O'Reilly AI London 2019 on a reinforcement learning approach Webber developed for public policy, and a YouTube video series introducing SageMaker.3

Teaching and writing

Webber wrote Pretrain Vision and Large Language Models in Python, published by Packt in 2023 as an end-to-end guide to building and deploying foundation models on AWS. The book moves from choosing use cases and datasets through distributed training with several kinds of parallelism, evaluation, detecting and mitigating bias, and deployment, and its companion repository holds the code examples.3

Trainium Frontier competition

In August 2026 Webber co-wrote the Amazon Science announcement of the AWS Trainium Frontier competition, which challenges researchers to train language models from scratch on Trainium chips and to co-design model architectures and kernels for the hardware, with a finalist ceremony during NeurIPS 2026.1

Work and contributions

Timeline

  1. Gave a keynote at O'Reilly AI London on a reinforcement learning approach for public policy.3
  2. Published the book Pretrain Vision and Large Language Models in Python with Packt.3
  3. Co-wrote the Amazon Science announcement of the AWS Trainium Frontier competition.1

Where they work

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References

3 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026

  1. AWS Trainium Frontier competition: Co-design models and kernels on purpose-built AI chipsAmazon Science · Announcement · published Aug 10, 2026 · accessed Oct 21, 2026
  2. EmilyWebber (Emily Webber) on GitHubGitHub · Official page · accessed Oct 21, 2026
  3. PacktPublishing/Pretrain-Vision-and-Large-Language-Models-in-Python README and licensePackt Publishing (GitHub repository) · Repository · accessed Oct 21, 2026