AWS Machine Learning Blog

MARCH 22, 2024

Before joining AWS, he worked for AWS customers and partners in software engineering, consulting, and architecture roles for 8+ years. In his free time he is pursuing a PhD in ML Engineering at University of Regensburg, focussing on applied NLP in the science domain.

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Large Language Models Natural Language Processing Software Engineer NLP 90

IBM Journey to AI blog

AUGUST 11, 2023

MLOps fosters greater collaboration between data scientists, software engineers and IT staff. Origins of the MLOps process MLOps was born out of the realization that ML lifecycle management was slow and difficult to scale for business application. How to use ML to automate the refining process into a cyclical ML process.

Data Science 145

Data Science DevOps Machine Learning Data Scientist 145

TensorFlow

MAY 11, 2023

Posted by Thad Starner (Professor, Georgia Tech and Staff Research Scientist, Google), Sam Sepah (ML Research Program Manager), Manfred Georg (Software Engineer, Google), Mark Sherwood (Senior Product Manager, Google), Glenn Cameron (Product Marketing Manager, Google) Over 70 million deaf people around the world use sign language to communicate.

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Software Engineer Large Language Models ML Engineer ML 98

AWS Machine Learning Blog

JANUARY 17, 2023

This development approach can be used in combination with other common software engineering best practices such as automated code deployments, tests, and CI/CD pipelines. Cory Hairston is a Software Engineer at the Amazon ML Solutions Lab. Marcelo Aberle is an ML Engineer in the AWS AI organization.

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Software Engineer ML Engineer ML Machine Learning 75

ODSC - Open Data Science

FEBRUARY 2, 2023

They’re looking for people who know all related skills, and have studied computer science and software engineering. As MLOps become more relevant to ML demand for strong software architecture skills will increase as well. While knowing Python, R, and SQL are expected, you’ll need to go beyond that.

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Data Science Data Scientist Big Data Machine Learning 98

TheSequence

JANUARY 19, 2024

You probably don’t need ML engineers In the last two years, the technical sophistication needed to build with AI has dropped dramatically. ML engineers used to be crucial to AI projects because you needed to train custom models from scratch. Instead, Twain employs linguists and salespeople as prompt engineers.

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Prompt Engineer Prompt Engineering Generative AI Large Language Models 59

ODSC - Open Data Science

FEBRUARY 20, 2023

We’ll also have a series of introductory sessions on AI literacy, intros to programming, etc.

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Data Science Machine Learning ML Engineer Python 96

Pickl AI

JULY 14, 2023

The average salary of a ML Engineer per annum is $125,087. Data Engineer: Data Engineers ae responsible for building systems that collect, manage and convert raw data into usable information for Data Scientists, business analysts and others. The average salary for a Robotics Engineer stands at $101,062.

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Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

AssemblyAI

DECEMBER 15, 2022

Shubham Saboo (Head of DevRel at Tenstorrent Inc. Final Words With our first-ever hackathon, we hoped to foster innovation and creativity for AI-first products.

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Software Engineer ML Engineer Data Scientist AI Chatbots 130

AWS Machine Learning Blog

FEBRUARY 13, 2024

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

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ML ML Engineer Machine Learning Data Scientist 107

Heartbeat

FEBRUARY 1, 2023

Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. In this article, we’ll learn everything there is to know about these operations and how ML engineers go about performing them. What is MLOps? They might also help with data preparation and cleaning.

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DevOps Machine Learning Data Scientist Software Engineer 96

ODSC - Open Data Science

MARCH 27, 2023

ML Governance: A Lean Approach Ryan Dawson | Principal Data Engineer | Thoughtworks Meissane Chami | Senior ML Engineer | Thoughtworks During this session, you’ll discuss the day-to-day realities of ML Governance. Scaling AI/ML Workloads with Ray Kai Fricke | Senior Software Engineer | Anyscale Inc.

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Machine Learning Data Ingestion ML Explainability 98

The MLOps Blog

SEPTEMBER 7, 2023

This situation is not different in the ML world. Data Scientists and ML Engineers typically write lots and lots of code. is an experiment tracker for ML teams that struggle with debugging and reproducing experiments, sharing results, and messy model handover. Aside neptune.ai

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Software Engineer Machine Learning ETL ML Engineer 52

ODSC - Open Data Science

FEBRUARY 22, 2024

By the end of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows. Using Graphs for Large Feature Engineering Pipelines Wes Madrigal | ML Engineer | Mad Consulting Feature engineering from raw entity-level data is complex, but there are ways to reduce that complexity.

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Machine Learning Data Science Python ML 52

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

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Data Scientist ML Data Science Automation 91

The MLOps Blog

JANUARY 23, 2023

Most of our customers are doing ML/MLOps at a reasonable scale, NOT at the hyperscale of big-tech FAANG companies. Not a fork: – The MLOps team should consist of a DevOps engineer, a backend software engineer, a data scientist, + regular software folks. How about the ML engineer? Let me explain.

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DevOps Metadata Software Engineer Data Scientist 59

Chatbots Life

MAY 12, 2023

We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers? Will ChatGPT replace ML Engineers? This makes the tool extremely useful as a software engineer's assistant.

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ChatGPT Software Engineer NLP Prompt Engineer 105

O'Reilly Media

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. Software Architecture. This approach is not novel.

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DevOps Software Engineer Data Scientist ML 138

AWS Machine Learning Blog

MARCH 9, 2023

As machine learning (ML) models have improved, data scientists, ML engineers and researchers have shifted more of their attention to defining and bettering data quality. This has led to the emergence of a data-centric approach to ML and various techniques to improve model performance by focusing on data requirements.

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ML Engineer Data Scientist Convolutional Neural Networks ML 77

AWS Machine Learning Blog

SEPTEMBER 29, 2023

This guest post is co-written by Lydia Lihui Zhang, Business Development Specialist, and Mansi Shah, Software Engineer/Data Scientist, at Planet Labs. Planet and AWS’s partnership on geospatial ML SageMaker geospatial capabilities empower data scientists and ML engineers to build, train, and deploy models using geospatial data.

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Machine Learning ML Data Scientist Python 114

The MLOps Blog

AUGUST 3, 2023

This is Piotr Niedźwiedź and Aurimas Griciūnas from neptune.ai , and you’re listening to ML Platform Podcast. Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. We thought, “how can we lower the software engineering bar?”

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ML Data Scientist Software Engineer Machine Learning 52

AWS Machine Learning Blog

APRIL 5, 2024

SageMaker geospatial capabilities make it straightforward for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. With over 15 years of experience, he supports customers globally in leveraging AI and ML for innovative solutions and building ML platforms on AWS.

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ML Data Scientist Python Machine Learning 106

ODSC - Open Data Science

FEBRUARY 24, 2023

Apache Superset GitHub | Website Apache Superset is a must-try project for any ML engineer, data scientist, or data analyst. Its goal is to help with a quick analysis of target characteristics, training vs testing data, and other such data characterization tasks.

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Data Analysis Business Intelligence Data Science Python 126

ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

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Machine Learning Data Drift Data Science ML Engineer 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

In this example, Code Editor can be used by an ML engineering team who needs advanced IDE features to debug their code and deploy the endpoint. We will deploy a Mistral-7B large language model (LLM) model into an Amazon SageMaker real-time endpoint using a built-in container from HuggingFace.

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Machine Learning ML LLM Software Engineer 104

AWS Machine Learning Blog

SEPTEMBER 25, 2023

Kemeng Zhang is an ML Engineer based in Zurich. She helps global customers design, develop, and scale ML-based applications to empower their digital capabilities to increase business revenue and reduce cost. He enjoys every aspect of software engineering, from design to implementation, and from deployment to maintenance.

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ML Machine Learning Software Engineer ML Engineer 87

AWS Machine Learning Blog

APRIL 26, 2023

The first is by using low-code or no-code ML services such as Amazon SageMaker Canvas , Amazon SageMaker Data Wrangler , Amazon SageMaker Autopilot , and Amazon SageMaker JumpStart to help data analysts prepare data, build models, and generate predictions. He has a background in software engineering and AI research.

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ML Machine Learning Data Science Data Drift 90

Viso.ai

MARCH 29, 2024

MLflow is an open-source platform designed to manage the entire machine learning lifecycle, making it easier for ML Engineers, Data Scientists, Software Developers, and everyone involved in the process. MLflow can be seen as a tool that fits within the MLOps (synonymous with DevOps) framework.

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Machine Learning ML Automation Data Scientist 52

The MLOps Blog

OCTOBER 3, 2023

I started from tech, my first job was an internship at Google as a software engineer. I’m from Poland, and I remember when I got an offer from Google to join as a regular software engineer. I see so many of these job seekers, especially on the MLOps side or the ML engineer side. It’s two things.

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ML Data Scientist Machine Learning Data Science 52

Mlearning.ai

AUGUST 18, 2023

As a software engineer your role is to write code for a certain cause. As a software developer the more versed you are in DevOps the better you can foresee issues, fix bugs and be a valued team member. As an ML engineer you’re in charge of some code/model. Same analogy applies to MLOps.

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DevOps Python ML ML Engineer 52

AWS Machine Learning Blog

FEBRUARY 5, 2024

SageMaker geospatial capabilities make it easy for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. With over 15 years of experience, he supports customers globally in leveraging AI and ML for innovative solutions that capitalize on geospatial data.

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ML Machine Learning Software Engineer Python 85

AWS Machine Learning Blog

OCTOBER 19, 2023

Amazon SageMaker provides purpose-built tools for ML teams to automate and standardize processes across the ML lifecycle. With a background in software engineering, she organically moved into an architecture role. The following diagram illustrates the SageMaker MLOps workflow.

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Machine Learning Python ML Automation 89

The MLOps Blog

AUGUST 4, 2023

Cross-functional collaboration Machine learning projects often involve collaboration between data scientists, ML engineers, and software engineers. Unification of coding standards Finally, machine learning teams often include members without a software engineering background.

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ML Machine Learning Python Software Engineer 52

The MLOps Blog

JUNE 27, 2023

Collaborative workflows : Dataset storage and versioning tools should support collaborative workflows, allowing multiple users to access and contribute to datasets simultaneously, ensuring efficient collaboration among ML engineers, data scientists, and other stakeholders. Check out the documentation to get started.

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Machine Learning Metadata Data Quality Data Scientist 134

The MLOps Blog

JULY 18, 2023

You have a bit of education in music composition, math, and science before you get more into the software engineering side of things. But you have started out in software design engineering, is that correct? So just to ask a little bit about your background here, you have a pretty interesting one.

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Conversational AI Natural Language Processing AI AI 52

The MLOps Blog

DECEMBER 28, 2022

Organization Gigaforce Inc Industry InsurTech provider Team size Gigaforce built an ML team three years ago in 2020 and has a team size of 5-7. Team composition The team comprises domain experts, data engineers, data scientists, and ML engineers.

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ML Data Scientist ML Engineer Machine Learning 78

Unite.AI

DECEMBER 15, 2023

My role at Prolific is split between being an advisor regarding AI use cases and opportunities, and being a more hands-on ML Engineer. I started my career in Software Engineering and have gradually transitioned to Machine Learning. What got you interested in AI?

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Machine Learning AI AI AI Modeling 130