spez
Joined 20 years ago
Joined 20 years ago
Reddit is hiring engineers in ads quality for our brand-new NYC office! We’re looking for machine learning and backend engineers, both junior and senior.
The ads quality team is responsible for all the machine learning that powers our ads backend, as well as the inference and ML serving infrastructure.
Our backend is in flux, but we’re using: Spark and Scala on AWS for machine learning, as well as BigQuery on GCP for analysis. Our ads serving stack is written in go and runs on AWS.
If you’re interested shoot us an email at [email protected]
Sometimes there is an explanation (e.g. the flight doesn't exist, or has a 30hr layover), and other times we don't have the flight, in which case we want to alert our providers to fix it.
I personally don't like working in frameworks of that size because I find myself fighting them to do what I want.
For the course itself, I really wanted the students to get as close to the server as possible. Then, when some of them switch to the heavier frameworks, they'll have a better idea of what the framework is doing and what is possible. The course had a time constraint on it as well.
All in all, your anecdote reenforces my feelings on the topic :)
I actually deliberately didn't use Django specifically because it's so complicated for beginners (and for pros, IMHO). I was trying to avoid magic. Webapp2, which is the web framework GAE users, and what we used in the course, is about as simple as you can get without starting from scratch.
The first thing we added was the "rising" page, which used to be reddit's default "new" page. The rising page was a weighted new page. It was a little hacky, but worked for a while. I see they've changed this, which I think may have been a mistake, but I haven't thought about it in forever.
The second thing we did, which worked really well, was to have an up-and-coming link placed at the top of the list on the frontpage. This helped those borderline posts get more visibility. I had a reddit simulator I used to use to test things like this. That space appears to be a subreddit search box for me, so it seems they've moved onto another solution.
Randomness is an interesting idea, though it might be a bit difficult to fit into the way we cached things.
Reddit is hiring engineers in ads ML for our brand-new NYC office. We’re looking for both junior and senior ML engineers.
The ads ML team is responsible for all the machine learning that powers our ads backend, as well as the inference and ML serving infrastructure.
Our backend is in flux, but we’re using: Spark and Scala on AWS for machine learning, as well as BigQuery on GCP for analysis.
Our ads serving stack is written in go and runs on AWS, and our ML includes logistic regression, GBDT, NLP embeddings, recommender systems, and more.
If you’re interested, shoot us an email at [email protected]