Unite.AI

JUNE 28, 2023

It became apparent to both Razi and me that we had the opportunity to make a significant impact by radically simplifying the feature engineering process and providing data scientists and ML engineers with the right tools and user experience for seamless feature experimentation and feature serving.

Data Scientist 264

Data Scientist Data Science Machine Learning ML Engineer 264

AWS Machine Learning Blog

APRIL 8, 2025

Integrating model deployment into the service development process was a key initiative to enable data scientists and ML engineers to deploy and maintain those models. The ML platform empowers the building and evolution of ML systems.

Machine Learning 98

Machine Learning ML Auto-complete Data Scientist 98

AWS Machine Learning Blog

SEPTEMBER 12, 2024

As generative AI moves from proofs of concept (POCs) to production, we’re seeing a massive shift in how businesses and consumers interact with data, information—and each other. While these layers provide different points of entry, the fundamental truth is that every generative AI journey starts at the foundational bottom layer.

Generative AI 96

Generative AI AI AI ML 96

AWS Machine Learning Blog

FEBRUARY 21, 2025

Deployment times stretched for months and required a team of three system engineers and four ML engineers to keep everything running smoothly. With just one part-time ML engineer for support, our average issue backlog with the vendor is practically non-existent.

Data Science 74

Data Science Data Scientist Data Ingestion DevOps 74

AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

ML 130

ML Data Scientist ML Engineer Data Science 130

AWS Machine Learning Blog

AUGUST 4, 2023

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

Data Scientist 92

Data Scientist ML ETL Data Platform 92

AWS Machine Learning Blog

FEBRUARY 27, 2024

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization.

Machine Learning 137

Machine Learning DevOps Data Scientist Data Quality 137