Software Engineer (Backend) - ML Effectiveness - Cortex
Who We Are:
Cortex is a team of software engineers and machine learning scientist to developing state-of-the-art machine learning capabilities to refine and transform our products.
Twitter is the heartbeat of the world: it is the only platform that offers insight into everything that is happening live. Our challenge: content that's posted on our platform is very rich, and our users' interests very diverse. Machine learning can help us connect users to the right content, and improve the quality of our products.
As a centralized machine learning team within Twitter, Cortex builds a platform bringing deep learning to all of Twitter BlueBird and Revenue products.
What You’ll Do:
You will work with our team of machine learning experts and software engineers to design some of the strongest machine learning platform in the world, based on the latest deep learning, and powered by Twitter data.
Part of your responsibilities will be to design abstractions and libraries, create APIs and tools to simplify the usage of these capabilities for all engineers (even those without machine learning knowledge) at Twitter. Other responsibilities include integration with the Twitter data stack to feed our models through the platform, as well as optimizing latencies.
Sample Work: https://blog.twitter.com/engineering/en_us/topics/insights/2018/ml-workflows.html
Who You Are:
You have a passion for machine learning and improving the ways people consume the world, live. You are excited to join an incredibly talented, and fun team which loves to take on new challenges. You like a fast-paced & fun environment, believe in Twitter’s mission in the world and want to be a core actor in pushing it forward.
Scala or Java experience
Good understanding of the JVM
Experience with distributed systems development
Experience with software engineering best practices (e.g. unit testing, code reviews, design documentation)
BS, MS, or PhD in Computer Science or equivalent work experience
Nice to have:
Python or Lua experience
Familiarity with machine learning concepts
After you apply, a recruiter may reach out to you for an introductory call.
If your background is a match for the role, you may phone interview with 1-2 people.
If you continue through the process, you will come onsite 1-2 times to interview with a total of 5-10 people.
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