4 ms·
My job title is ML Engineer, but my day to day job is almost pure software engineering. I build the systems to support ML systems in production. As others have
by angarg12 2y ago
My job title is ML Engineer, but my day to day job is almost pure software engineering.
I build the systems to support ML systems in production. As others have mentioned, this includes mostly data transformation, model training, and model serving.
Our job is also to support scientists to do their job, either by building tools or modifying existing systems.
However, looking outside, I think my company is an outlier. It seems in the industry the expectations for a ML Engineer are more aligned to what a data/applied scientist does (e.g. building and testing models). That introduces a lot of ambiguity into the expectations for each role in each company.
- hnthrowaway0328 2y agoThat's really the kind of job I'd love. Whatever the data is, I don't care. I make sure that the users get the correct data quickly.
- tedivm 2y agoIn my experience your company is doing it right, and doing it the way that other successful companies do. I gave a talk at the Open Source Summit on MLOps in April, and one of the big points I try to drive home is that it's 80% software development and 20% ML. https://www.youtube.com/watch?v=pyJhQJgO8So https://www.youtube.com/watch?v=pyJhQJgO8So
- exegete 2y agoMy company is largely the same. I’m an MLE and partner with data scientists. I don’t train or validate the models. I productionize and instrument the feature engineering pipelines and model deployments. More data engineering and MLOps than anything. I’m in a highly regulated industry so the data scientists have many compliance tasks related to the models and we engineers have our own compliance tasks related to the deployments. I was an MLE at another company in the very same industry before and did everything in the model lifecycle and it was just too much.