2023 ML Engineer Prompt Engineering 
The MLOps Blog
JUNE 27, 2023
As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.
Snorkel AI
MAY 4, 2023
Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. AI development stack: AutoML, ML frameworks, no-code/low-code development. The post Use your data to build your AI moat: The Future of Data-Centric AI 2023 appeared first on Snorkel AI. Explore the full agenda here.
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Snorkel AI
MAY 4, 2023
Join us on June 7-8 to learn how to use your data to build your AI moat at The Future of Data-Centric AI 2023. AI development stack: AutoML, ML frameworks, no-code/low-code development. The post Use your data to build your AI moat: The Future of Data-Centric AI 2023 appeared first on Snorkel AI. Explore the full agenda here.
Towards AI
SEPTEMBER 22, 2023
Last Updated on September 23, 2023 by Editorial Team Author(s): Kelvin Lu Originally published on Towards AI. One example is prompt engineering. Prompt engineering has proved to be very useful. Some people foresaw the emergence of prompt engineer as a new title. Is this the future of the ML engineer?
AWS Machine Learning Blog
NOVEMBER 29, 2023
Since launching in June 2023, the AWS Generative AI Innovation Center team of strategists, data scientists, machine learning (ML) engineers, and solutions architects have worked with hundreds of customers worldwide, and helped them ideate, prioritize, and build bespoke solutions that harness the power of generative AI.
AWS Machine Learning Blog
SEPTEMBER 1, 2023
After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. These users need strong end-to-end ML and data science expertise and knowledge of model deployment and inference.
Snorkel AI
JUNE 9, 2023
Among other topics, he highlighted how visual prompts and parameter-efficient models enable rapid iteration for improved data quality and model performance. He also described a near future where large companies will augment the performance of their finance and tax professionals with large language models, co-pilots, and AI agents.
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