IBM Journey to AI blog

JULY 30, 2024

AI Developer / Software engineers: Provide user-interface, front-end application and scalability support. Organizations in which AI developers or software engineers are involved in the stage of developing AI use cases are much more likely to reach mature levels of AI implementation.

Generative AI 266

Generative AI Data Scientist Software Engineer AI 266

ODSC - Open Data Science

MARCH 12, 2025

AI engineering extended this by integrating AI systems more deeply into software engineering pipelines, making it a crucial field as AI applications became more sophisticated and embedded in real-world systems.

Data Science 52

Data Science ETL Machine Learning AI Engineer 52

AWS Machine Learning Blog

MARCH 5, 2025

By following these guidelines, organizations can follow responsible AI best practices for creating high-quality ground truth datasets for deterministic evaluation of question-answering assistants. Philippe Duplessis-Guindon is a cloud consultant at AWS, where he has worked on a wide range of generative AI projects.

Generative AI 76

Generative AI LLM AI AI 76

ODSC - Open Data Science

JULY 19, 2023

Data Estate: This element represents the organizational data estate, potential data sources, and targets for a data science project. Data Engineers would be the primary owners of this element of the MLOps v2 lifecycle. The Azure data platforms in this diagram are neither exhaustive nor prescriptive.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

ODSC - Open Data Science

MARCH 18, 2025

Since 2022, she has been driving digital transformation, designing cloud architectures, and developing cutting-edge data platforms incorporating IoT, real-time analytics, machine learning, and generative AI. It will demonstrate model creation, model tuning, model evaluation, and model interpretation.

Data Science 64

Data Science Machine Learning Software Engineer Data Scientist 64

The MLOps Blog

MARCH 21, 2023

Automation You want the ML models to keep running in a healthy state without the data scientists incurring much overhead in moving them across the different lifecycle phases. It would make sure that all development and deployment workflows use good software engineering practices. My Story DevOps Engineers Who they are?

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69