Builders & open source
Emily Webber
Principal machine learning specialist solutions architect, AWS Trainium team, Amazon
- Principal machine learning specialist solutions architect, AWS Trainium team, Amazon Web Services (Annapurna Labs)12
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
Pretrain Vision and Large Language Models in Python (book and companion code) Open-source code
Author of the 2023 Packt book; the MIT-licensed companion repository covers dataset and model preparation, distributed training on SageMaker, fine-tuning and evaluation, bias detection, hosting and MLOps.32
AWS Trainium Frontier competition
Co-author of the August 2026 Amazon Science announcement of the competition, which asks teams to co-design language models and kernels for Trainium chips.1
Timeline
Where they work
- Amazon 39 people in the wiki
Related people
- Mu LiAlso at Amazon
- Julien SimonAlso at Amazon
- Allie K. MillerAlso at Amazon
- Alex SmolaAlso at Amazon
- Antje BarthAlso at Amazon
- Linus SebastianTeaching and writing · Chips and hardware
- Sean LieChips and hardware · Training systems
- Stephen BalabanChips and hardware · Training systems
- Zack NelsonTeaching and writing · Chips and hardware
- Cully CavnessChips and hardware · Training systems
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References
3 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026