We Raised $8M Series A to Continue Building Experiment Tracking and Model Registry That “Just Works”
Write articles for the Neptune Blog
Why write for us?
Interested in writing technical articles for Data Scientists and Machine Learning Engineers?
Would you like to share your knowledge with the ML community?
Would like to have your work promoted all over the web and seen by thousands of people? Almost 200k a month to be exact, no bragging, just saying how it is:)
Want to make an extra buck on the side?
Write great articles for Neptune and see what happens!
Who are we looking for?
We’re searching for ML practitioners. So if you’re a Data Scientist or an ML Engineer, and you’re experienced in both training models and moving them to production – this is something for you.
Don’t worry if you’re not a pro in technical writing. We’ll connect you with an editor, an SEO advisor, and a designer if needed. The primary goal for us is to let ML folks share their knowledge with other ML folks.
How much does it pay?
As usual, the answer in such cases is “it depends”. For each article, we suggest a rate based on the topic idea, the scope of the article, and its relevance to the ML community and the Neptune product. Either way, we agree on the final number before you start writing.
In general, rates vary between $300-600 per article.
Who am I writing for?
We’re looking for content that speaks to data scientists, machine learning engineers, and data science managers. Our focus is on the more advanced stuff.
What should I write about?
We have a big list of topics that we would love people to write about so you can pick a topic from this list.
Some example topics to get your creative juices flowing:
- MLOps: best practices in moving models from research to production, project organization, examples of MLOps tool stacks, etc. (examples)
- Model development: building models, selection and evaluation of models, hyperparameter tuning, experiment tracking, data versioning, etc. (examples)
- Model management: model deployment, model versioning, model monitoring, etc. (examples)
- Building MLOps tool stack: comparisons of tool, lists of best tools for specific tasks, evaluation stories (examples)
We want to cover different ML areas, including Computer Vision, NLP, Reinforcement Learning, or Time Series.
We’re also open to your amazing ideas: pitch your idea, maybe it’s better than anything we wrote before!
When it comes to style you can write:
- Technical blog posts:
Check out our blog to see more examples!
How do I get started?
Interested in writing for us? Here’s what the next steps look like:
- Apply: Send an email to guestwriters@neptune.ai with some info about you, examples of posts you wrote before (if you wrote any), your LinkedIn/Medium/Github profile, article topic idea (if you have one). Without this information, we’re not able to know if we’re a good match. So make sure to mention it in the email.
- Wait for our response: We review your profile and contact you with more information. We only contact selected candidates.
- Agree on the topic and scope: We figure out what you will write about, at what price, and do some paperwork.
- Write: You can start writing! Create the first draft in a Google doc. It doesn’t have to be perfect yet.
- Refine: We iterate over the draft to make it great (unless it already is :)). Edits, improvements, and tweaks happen here.
- Get paid: Once we are both happy with the final version of the article (yes, you approve it too), we finalize the contract and send the cash over.
- Get published and promoted: We take care of this.
- Repeat: Any time you feel like writing for the Neptune blog again, you just let us know!