Auto-complete DevOps ML Engineer 
AWS Machine Learning Blog
APRIL 8, 2025
The following diagram illustrates iFoods updated architecture, which incorporates an internal ML platform built to streamline workflows between data science and engineering teams, enabling efficient deployment of machine learning models into production systems. The ML platform empowers the building and evolution of ML systems.
AWS Machine Learning Blog
SEPTEMBER 4, 2024
Its scalability and load-balancing capabilities make it ideal for handling the variable workloads typical of machine learning (ML) applications. SageMaker simplifies the process of managing dependencies, container images, auto scaling, and monitoring. They often work with DevOps engineers to operate those pipelines.
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AWS Machine Learning Blog
JANUARY 5, 2024
This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.
The MLOps Blog
JANUARY 23, 2023
Lived through the DevOps revolution. Came to ML from software. Founded neptune.ai , a modular MLOps component for ML metadata store , aka “experiment tracker + model registry”. Most of our customers are doing ML/MLOps at a reasonable scale, NOT at the hyperscale of big-tech FAANG companies. Some are my 3–4 year bets.
AWS Machine Learning Blog
NOVEMBER 9, 2023
Create a KMS key in the dev account and give access to the prod account Complete the following steps to create a KMS key in the dev account: On the AWS KMS console, choose Customer managed keys in the navigation pane. Choose Create key. For Key type , select Symmetric. For Script Path , enter Jenkinsfile. Choose Save.
Mlearning.ai
MAY 3, 2023
autogpt : Auto-GPT is an “Autonomous AI agent” that given a goal in natural language, will allow Large Language Models (LLMs) to think, plan, and execute actions for us autonomously. The complete code of the APP can be found here. It is built on top of OpenAI’s Generative Pretrained Transformer (GPT-3.5 If you liked the blog post pls.
The MLOps Blog
JUNE 27, 2023
Can you see the complete model lineage with data/models/experiments used downstream? Some of its features include a data labeling workforce, annotation workflows, active learning and auto-labeling, scalability and infrastructure, and so on. MLOps workflows for computer vision and ML teams Use-case-centric annotations.
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