MLops is the new career path in cloud computing

ClearML, an open-source MLops platform, has announced its new research report: “MLops in 2023: What does the future hold?” This study surveyed 200 machine learning decision makers in the United States, examining key trends in machine learning and MLops (machine learning operations).

Putting potential vendor bias aside for now, ClearML’s research found that MLops is now enjoying widespread adoption within enterprises; 85% of respondents said they have a dedicated MLops budget in 2022. And 14% said they don’t have a budget in place but expect to do so in 2023. So companies are turning to MLops now or soon.

In case you haven’t noticed, operations seem to be the new focus of cloud computing work. We have cloud computing (cloud operations), finops (financial transactions), devops (development and operations), and secops (security operations). You can see the trend.

It’s for good reason. Creating and deploying cloud solutions or migrating existing solutions to the cloud are necessary tasks. Normally they are one and done. Then the focus is on operations to get the value of that work back to the business. As many companies have discovered over the past few years, just throwing things on a public cloud provider and hoping for the best doesn’t pay off. Neglecting operations – all operations – results in huge cost overruns and little return on investment.

MLops is an essential component of the machine learning lifecycle, enabling organizations to manage and operate machine learning models in production. MLops processes ensure that models are deployed, monitored, and updated consistently and efficiently, allowing organizations to take full advantage of machine learning. Applications that can leverage ML as an innovative differentiator can add tremendous value to the business, well beyond investing in ML-enabled systems.

MLops is becoming the hottest career path of late due to the new reliance on AI/ML augmented business systems that drive intelligent supply chains, detect fraud and provide marketing and sales analysis. Of course, one only has to look at the buzz around ChatGPT to see the interest and potential of weaponizing AI to drive bigger profits, but that’s really been changing over the past 20 years.

What are the main tasks involved in MLops? What would you be working on day to day if you moved into a job related to MLops?

  • Model deployment: deploy machine learning models in a production environment, making them accessible to business applications
  • Model follow: evaluate the performance of the model once it is deployed to ensure that it provides the desired results
  • Version management: keep track of different versions of models as they evolve and improve over time
  • Model recycling: update the model with new data to ensure it remains accurate and relevant when the data becomes stale, decreases in performance, or exhibits bias
  • Trial: ensure that a model works optimally
  • Automating: automate tasks such as model deployment, monitoring, and recycling to reduce the time and effort needed to manage models and free up valuable resources for other tasks

Having performed each of these tasks at some point in my career, none of what I’ve listed is that difficult to understand. Usually MLops is part of the existing cloudps team, but this will require special training in machine learning in general, as well as company-specific ML systems. Then just follow the processes and procedures to keep the ML system running and updated.

Another reason why this is becoming a hot job ticket right now: if machine learning systems are not properly operated and maintained, the business can run into major problems. These can range from a misdirected marketing campaign that wastes millions of dollars to lawsuits resulting from a bias in a machine learning system that approves or denies families home loans. Many things can and will go wrong. Having the right MLops talent in place will reduce the risk.

Is MLops for you? If you’re looking for a higher-paying career that requires new and ongoing training, and you’re interested in ML as a technology, this could be the most fun and lucrative job you can get right now.

Copyright © 2023 IDG Communications, Inc.

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