Software Engineer - Machine Learning Core Environment - Cortex
Who We Are:
Cortex is a team of software engineers, data scientists, and research scientists dedicated 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.
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.
- 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
- Familiarity with TensorFlow
- Familiar with Machine Learning and/or Deep Learning
- Experience with CUDA (GP-GPU) programming
Engineering Hiring Process
Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.
If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.
If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.
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