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MLOps Engineer

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May 3, 2024 Updated June 7, 2024 4 minute read
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MLOps Engineers are responsible for the deployment and management of machine learning models. They work with data scientists and software engineers to ensure that models are deployed and managed in a way that maximizes their performance and minimizes their risk.

What does an MLOps Engineer do?

MLOps Engineers perform a variety of tasks, including:

  • Deploying and managing machine learning models
  • Monitoring model performance and identifying issues
  • Automating the deployment and management process
  • Working with data scientists and software engineers to improve model performance

What skills do I need to become an MLOps Engineer?

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Salaries for MLOps Engineer

City
Median
New York
$183,000
San Francisco
$202,000
Seattle
$190,000
See all salaries
City
Median
New York
$183,000
San Francisco
$202,000
Seattle
$190,000
Austin
$187,000
Toronto
$146,000
London
£95,000
Paris
€72,000
Berlin
€113,000
Tel Aviv
₪533,000
Singapore
S$155,000
Beijing
¥719,000
Shanghai
¥275,000
Bengalaru
₹1,012,000
Delhi
₹2,282,000
Bars indicate relevance. All salaries presented are estimates. Completion of this course does not guarantee or imply job placement or career outcomes.

Path to MLOps Engineer

Take the first step.
We've curated 16 courses to help you on your path to MLOps Engineer. Use these to develop your skills, build background knowledge, and put what you learn to practice.
Sorted from most relevant to least relevant:

Reading list

We haven't picked any books for this reading list yet.
Cover image
Mining of Massive Datasets
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Provides a comprehensive overview of MLOps engineering. It covers topics such as CI/CD pipelines, model governance, and security.
Mining of Massive Datasets
Hardcover
$$$
Mining of Massive Datasets
Kindle Edition
$$$
Mining of Massive Datasets
Hardcover
$$$
Mining of Massive Datasets
Hardcover
$$$
Mining of Massive Datasets
Kindle Edition
$$$
Cover image
Introducing MLOps
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Provides a step-by-step guide to building, deploying, and monitoring ML models in production. It covers topics such as data engineering, model deployment, and monitoring.
Introducing MLOps: How to Scale Machine Learning in...
Paperback
$$
Introducing MLOps: How to Scale Machine Learning in...
Kindle Edition
$$
Cover image
Deep Learning
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Covers the principles of deep learning. It introduces different neural network architectures and training algorithms, as well as applications of deep learning to different fields.
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Machine Learning
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Practical guide to MLOps for data science teams. It covers topics such as model monitoring, data quality, and infrastructure management.
Machine Learning
Paperback
Check
Machine Learning
Kindle Edition
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Cover image
Advances in Financial Machine Learning
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Covers machine learning algorithms in finance. It provides a solid fundamental understanding of financial data, especially time series.
Advances in Financial Machine Learning
Hardcover
$$
Advances in Financial Machine Learning
Kindle Edition
$$
Relevant careers
Machine Learning Engineer
Data Scientist
Software Engineer
Related topics
MLOps
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