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Projects vs. Open Source - which is better for my career?

Machine Learning Engineer at Taro Community profile pic
Machine Learning Engineer at Taro Community

TL;DR Contribute to Open Source ML or do side projects for ML. Which do you suggest is the better option?

I just started a new job, but due to circumstances (visa, tough market), I had to take the first job I could take and I ended up in a devops/production support role where I cant really write much code or write any production code (literally dont have access to dev code). I dont plan to stay here long (>6 months).

I read the infamous "" post and wanted to do side projects so that I am not rusty

Context on me: 80% of my background is in Applied ML/Data Science and 20% is software engineering. I am interested in pursuing as an ML Engineer/Data Scientist

Open Source

Pros

  • Tons of open source ML stuff supported by big tech companies
    • Meta has a ton of OS projects
  • Huggingface is open source
    • Lot of companies use ML models from huggingface (for e.g. BERT for NLP). Would contributing to this on huggingface be seen as impressive?
  • Exposure to working on large codebases, good software engineering practice as well

Cons

  • Minimal Impact
  • Hard to showcase my achievements, especially on LinkedIn

Projects

Pros

  • Ability to make and measure impact
  • easy to showcase
  • learn a lot

Cons

  • For ML, projects with impact is hard to do. Most ML applications is based on improving current products using existing data
  • Experience from building ML projects might not translate to what I would do on the job as a lot of it involves working with Engineering around data
  • It takes time and a lot of effort to have a ton of downloads
  • Can end up taking a lot of non-ML work work (web design/frontend) which is not relevant to MLE

Final question: If I were to do open source, what is the best way to showcase on LinkedIn?

  • Do you suggest adding the company you did OS for under the experience section and saying "Open Source Contributor"? My concern with this is that it may sound scammy/shady
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Posted a year ago
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