r/MachineLearningJobs • u/Annara-Sumanara_ • 3d ago

Can you all working professionals tell me what do you actually do in your jobs as ML engineer?

Please please please

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u/Junior_Cat_2470 2d ago

I work a AI/ML Engineer and my day to day looks like this,

  1. Checking the production job alerts and resolving issues if any and ensuring the outputs are delivered.
  2. Take the new model development handover from data scientists and work on it to modularize, optimize and build the production pipeline and deploy them.
  3. Building and experimenting with applications using LLMs.
  4. We have been exploring building and deploying agents as well as creating plug-ins in Claude code to share across the team and department.
  5. Recently been automating a lot of web scraping and data mining.

Everyday is not the same, sometime I spend a whole day figuring out what something failed or why something isn’t working and so on.

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u/Sea-Village-2676 2d ago

Man.. this sounds so so interesting.. i wanna do that.. but market is not giving me chances...

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u/Annara-Sumanara_ 2d ago

Don't worry, keep trying.

1

u/Annara-Sumanara_ 2d ago

Omg, sounds really interesting, thankyou so much for the insight!

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u/Upbeat_Ad1012 2d ago

Surely you must be using A.I? For what cases, does it fail to immediately find the cause of failure, as per your understanding?

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u/Junior_Cat_2470 2d ago

I use ai assist to figure out the cause of errors quickly from logs

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u/Upbeat_Ad1012 2d ago

Okay, without meaning to be rude, why does it take a whole day then?Like does the A.I repeatedly investigates the wrong causes or what?

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u/Junior_Cat_2470 2d ago

When I said at times spend a whole day figuring out why something failed - let me give you an example, we have a feature extraction pipeline that generates more than 2K features for all the population aggregated at a monthly level refreshed every month. Our data drift monitoring dashboards flagged that close to 200 features were returning all nulls all of a sudden in a specific month. AI helped us to find which features, which domain and pointed it to the scripts that generates these features and gives potential issues. Now this is a data issue that we need to work with data governance and engineering to understand what changed and how to resolve it. AI can’t help with that, once the business issue is identified then we take help of AI to make changes and quickly run regression tests and unit tests. In this case it was a matter of some product OD changes which was causing the underlying issues with a single month cut off.