Personally I prefer more declarative dependency configuration. Also the IntelliJ integration is terrible. It thinks so many of the files have syntax errors and doesn’t have reliable autocomplete or goto definition. Also I don’t like how many files there are; though to be fair i don’t know how standard our setup is.
On hiring: Python Paradox comes to mind (http://www.paulgraham.com/pypar.html).
I've never met sub-par FPer or Scala programmer specifically.
Using PHP or Javascript might give you a bigger top of the hiring funnel, but it doesn't mean you'll have easier time finding well-qualified applicant.
I have learned from an Amazon recruiter that it was a data-driven decision to focus on algorithms during interviews. Apparently, on average, it has worked the best for them than other ways of interviewing.
I think the state of despair is caused by companies copying practices from FAANGs without understanding the intricacies of why those practices are in place. To the point of asking a UX/UI dev to solve a DP problem.
Service-based and async architecture systems engineer.
7+ years in the industry / CS undergrad.
AI / reinforcement learning as a hobby (completed specialization on Coursera).
Location: Portland, OR (US Citizen)
Remote: Yes
Willing to relocate: Yes
Technologies:
-> Languages: Scala, Haskell, Rust (but I've used about 10 different languages over the years)
> The last few books I read were mostly filled with fluff, anecdotes, stories, jokes, and trivialities. Even if I wanted to read books, I just don't know which ones I should start with, out of the 1000 "must-read" books in my reading list.
I'm looking to continue working on scalable systems aimed at handing millions of users.
7+ years in the industry / CS undergrad.
Experience working at both startups and large enterprises.
AI / reinforcement learning as a hobby (completed specialization on Coursera).
Location: Portland, OR (US Citizen)
Remote: willing to try (3+ years of experience working with remote teammates)
Willing to relocate: would consider Seattle if the opportunity is an excellent fit.
Technologies:
-> Languages: Scala, Haskell, Rust (but I've used about 10 different languages over the years)
-> Async architecture toolbox: Kafka, RabbitMQ, SQS/SNS
-> Big Data stack: Spark, Hive, HBase
-> ML/RL: PyTorch
Résumé: https://drive.google.com/open?id=1YHWh4Fi6bur1mQg3U6FBUXIlb_-8H7-8
LinkedIn: https://www.linkedin.com/in/maxchistokletov/
Email: I'll share it if you ping me on LinkedIn. Or you can find it in my résumé.
I build scalable service-based systems capable of handing millions of users (most recently at Nike).
7+ years in the industry / CS undergrad.
Experience working at both startups and large enterprises.
AI / reinforcement learning as a hobby (completed specialization on Coursera).
Location: Portland, OR (US Citizen)
Remote: willing to try (3+ years experience working with distributed teams)
Willing to relocate: open to ideas, but won't move to SF Bay Area or LA.
Technologies:
-> Preferred languages: Scala, Haskell, Rust
-> Async architecture toolbox: Kafka, RabbitMQ, SQS/SNS
-> Big Data stack: Spark, Hive, HBase
-> RL: PyTorch
LinkedIn: https://www.linkedin.com/in/maxchistokletov/
Email: Just reach out to me through LinkedIn. I will be happy to share my email if necessary. Or reply here.
Highly recommend.