I'm curious about the day-to-day of a Machine Learning engineer. If you work in this field, could you share what your typical tasks and projects look like? What are you working on?
Ask HN: Machine learning engineers, what do you do at work?
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Re: Ask HN: Machine learning engineers, what do you do at work?
#2The opposite of what you’d think when studying machine learning…
95% of the job is data cleaning, joining datasets together and feature engineering. 5% is fitting and testing models.
Re: Ask HN: Machine learning engineers, what do you do at work?
#3The opposite of what you’d think when studying machine learning… 95% of the job is data cleaning, joining datasets together and feature engineering. 5% is fitting and testing models.
Sounds like a Data Scientist job?
Re: Ask HN: Machine learning engineers, what do you do at work?
#4The amount of response may be self explaining.
Not my main work, but spending a lot of time gluing things together. Tweaking existing open source. Figuring out how to optimize resources, retraining models on different data sets. Trying to run poorly put together python code. Adding missing requirements files. Cleaning up data. Wondering what could in fact really be useful to solve with ML that hasn't been done years ago already. Browsing the prices of the newest GPUs and calculating whether that would be worth it to get one rather than renting overpriced hours off hosting providers. Reading papers until my head hurt, that is just 1 by 1, by the time I finish the abstract and glanced over a few diagrams in the middle.
Re: Ask HN: Machine learning engineers, what do you do at work?
#5pip install pytorch
Environment broken
Spend 4 hours fixing python environment
pip install Pillow
Something something incorrect cpu architecture for your Macbook
Spend another 4 hours reinstalling everything from scratch after nuking every single mention of python
pip install … oh time to go home!
Re: Ask HN: Machine learning engineers, what do you do at work?
#6The opposite of what you’d think when studying machine learning… 95% of the job is data cleaning, joining datasets together and feature engineering. 5% is fitting and testing models.
Sounds like a Data Scientist job?
This is a large problem in industry: defining away some of the most important parts of a job or role as (should be) someone else's.
There is a lot of toil and unnecessary toil in the whole data field, but if you define away all of the "yucky" parts, you might find that all of those "someone elses" will end up eating your lunch.
Re: Ask HN: Machine learning engineers, what do you do at work?
#7[deleted]
Re: Ask HN: Machine learning engineers, what do you do at work?
#8pip install pytorch Environment broken Spend 4 hours fixing python environment pip install Pillow Something something incorrect cpu architecture for your Macbook Spend another 4 hours reinstalling everything from scratch after nuking every single mention of python pip install … oh time to go home!
Maybe pip should not work by default (but python -m venv then pip install should)
Re: Ask HN: Machine learning engineers, what do you do at work?
#9pip install pytorch Environment broken Spend 4 hours fixing python environment pip install Pillow Something something incorrect cpu architecture for your Macbook Spend another 4 hours reinstalling everything from scratch after nuking every single mention of python pip install … oh time to go home!
If you're still doing ML locally in 2024 and also use an ARM macbook, you're asking for trouble.
Re: Ask HN: Machine learning engineers, what do you do at work?
#10pip install pytorch Environment broken Spend 4 hours fixing python environment pip install Pillow Something something incorrect cpu architecture for your Macbook Spend another 4 hours reinstalling everything from scratch after nuking every single mention of python pip install … oh time to go home!
Maybe pip should not work by default (but python -m venv then pip install should)
Legends say there were times when you'd have a program.c file and just run cc program.c, and then could just execute the compiled result. Funny that programmer's job is highly automatable, yet we invent ourselves tons of intermediate layers which we absolutely have to deal with manually.