Tag: Machine Learning Engineer

April 30, 2024

What reads impacted my ML Engineering Journey most?

This blog is written by Vishnu Rachakonda , a Data Scientist at FirstHand. Why I’m writing this Inspired by Ben Kuhn’s Essays on programming I think about a lot , I put together a list of the most influential reads on my journey as a machine learning engineer. I would highly recommend all of these essays as must-reads for MLEs at any stage of their career.

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April 30, 2024

What does Frata do? A Machine Learning Engineer tells all.

💡 This is a project for the MLOps Community to fully understand what different people touching ML do at their jobs. We want to find out what their day-to-day looks like. From the most granular to the most mundane, they tell us everything! This is our chance to bring clarity to the different parts of MLOps ranging from big companies to small startups.

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April 30, 2024

What Does James Lamb – A Machine Learning Engineer Do?

💡 This is a project for the MLOps Community to fully understand what different people do at their jobs. We want to find out what your day-to-day looks like. From the most granular to the most mundane, please tell us everything! This is our chance to bring clarity around the different parts of MLOps ranging from big companies to small start-ups.

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April 30, 2024

What does a Machine Learning Engineer at Etsy Do?

What does a Machine Learning Engineer do at Etsy? This is a project for the MLOps Community to fully understand what different people touching ML do at their jobs. We want to find out what their day-to-day looks like. From the most granular to the most mundane, they tell us everything! This is our chance to bring clarity to the different parts of MLOps ranging from big companies to small startups.

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April 30, 2024

What does a Machine Learning Engineer at DPG Media Do?

This is a project for the MLOps Community to fully understand what Machine Learning Engineers do at their jobs. We want to find out what your day-to-day looks like from the most granular to the most mundane, please tell us everything! This is our chance to bring clarity around the different parts of MLOps ranging from big companies to small start-ups. This is the fouth edition in this series.

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April 30, 2024

Challenges of Feature Monitoring for Real-Time Machine Learning

To be successful with machine learning, you need to do more than just monitor your models at prediction time. You also need to monitor your features and prevent a “garbage in, garbage out” situation. However, it’s extremely hard to detect problems with the data being served to your models.

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April 30, 2024

MLOps Maturity Assessment

Author: Vechtomova Maria As more and more companies rely on machine learning to run their daily operations, it’s becoming important to adopt MLOps best practices. However, it can be hard to find structured information on what those best practices actually are and how a company can become more mature in terms of MLOps if they decide to start on that journey. Microsoft’s MLOps maturity model or Google’s definition of MLOps levels is a good start, but they don’t necessarily offer actionable insights on how a project can go from being MLOps immature to achieving 100% MLOps maturity.

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April 30, 2024

“It worked when I prompted it” or the challenges of building an LLM Product

How do we serve a response with confidence, if we don’t know how confident we should be about the response? Author: Soham Chatterjee Over the last few weeks, we have been trying to build an LLM product ourselves, a Chrome extension aimed at improving English writing skills for non-native speakers , to see the challenges of taking an LLM to production. Our extension is free to use and open-source. All you need is an OpenAI API key.

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April 30, 2024

The Role of AI Safety Standards in Modern MLOps

With the recent explosive growth of AI, particularly in Generative AI, the importance of safety and reliability has surged as a paramount concern for businesses, consumers, and regulatory bodies. Recent safety standards and regulations as outlined in the EU AI Act and Biden’s executive order underscore the imperative to ensuring safe and trustworthy AI. Furthermore, the existence of over 20 ISO standards dedicated to AI safety presents a formidable challenge in integrating them effectively into operational frameworks.

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