Software Engineer - Machine Learning Core Environment - Cortex

San Francisco, CA

Who We Are:

Cortex enables, accelerates and grows machine learning at Twitter. The Machine Learning Core Environment team has the following mission: Improve online ML pipelines’ robustness, monitoring and maintenance for all teams by building tools that leverage Twitter’s infra and services that facilitate deployment.


In practice, the ML Core Environment team implements and maintains services that allow the whole company to run their models using a unified API, and creates and maintains libraries that make it easy to train, analyze, deploy and run models from within the Twitter infrastructure. By doing so, the team can improve the velocity of machine learning iteration and standardize, for example, observability for machine learning, online learning or distributed graph computation.


As a component of the ML platform work, the design of this software and a special focus on the stability of its APIs is paramount. This is a challenging and exciting area, with a unique opportunity to create advanced technologies in uncharted territories while having a large impact.


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.

 

What You’ll Do:

You will work with our team of machine learning experts and software engineers to design, architect and maintain the next iterations or our deep learning platform, used all through the company and within our latest products. You will be a cornerstone in transforming Twitter through machine learning. You will have the option to work closely with our internal customers, as well as contribute to the open source community.


Requirements:

  • Extensive experience with low-level programming (C, C++, Vectorization, …)
  • Experience with software engineering best practices (e.g. unit testing, code reviews, design documentation)
  • Strong algorithms and data structures background
  • BS, MS, or PhD in Computer Science, Electrical Engineering or equivalent work experience
  • Experience with ML frameworks (TensorFlow, …)


Desired:

  • Familiarity with TensorFlow
  • Familiar with Machine Learning and/or Deep Learning
  • Experience with CUDA (GP-GPU) programming


Hiring Process

Step 1

After you apply, a recruiter may reach out to you for an introductory call.

Step 2

If your background is a match for the role, you may phone interview with 1-2 people.

Step 3

If you continue through the process, you will come onsite 1-2 times to interview with a total of 5-10 people.

Application

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