Machine Learning Engineering Intern (PhD candidates)
Posted on: June 23, 2022
Twitter is where you go to talk about what's happening; it carries
some of the most important commentary and conversations and
mobilizes people into action.
Joining the team today means you'll have an impact on the
conversation of tomorrow.
We want every Tweep regardless of location or job to understand
their role in creating a culture where everyone is empowered to
bring their full authentic selves to work, experience belonging,
and do the best work of their career.
Working with the DisCo team at Twitter is about showing users the
content they care about. Our mission is to instantly connect users
to the information most meaningful to them. Realizing this involves
work in areas such as machine learning, applied data science,
recommendation systems, information retrieval systems, natural
language processing, large graph analysis, spam, and more. We build
relevance and machine learning models and systems to power the core
of the Twitter product and growth. As a graduate intern, you will
participate in all areas of our work, and be exposed to various
aspects of our team's capabilities and disciplines.
- Pursuing a Master's or Ph.D. in Machine Learning, Engineering
Computer Science or a related field
- Shows proficiency in the following languages Java, Python, C++,
Scala, Deep Learning, Machine Learning, Neural Networks,
Recommender Systems, Ranking, Information Retrieval, Reinforcement
Learning, TensorFlow, PyTorch
- Ability to take on complex problems, learn quickly, iterate, and
persist towards a good solution
We are committed to an inclusive and diverse Twitter. Twitter is an
equal opportunity employer. We do not discriminate based on race,
ethnicity, color, ancestry, national origin, religion, sex, sexual
orientation, gender identity, age, disability, veteran status,
genetic information, marital status or any other legally protected
status. All your information will be kept confidential according to
Keywords: Twitter, Glendale , Machine Learning Engineering Intern (PhD candidates), Engineering , Glendale, Arizona
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