Machine Learning Software Engineer - Applied Research

London

Who we are

Twitter has become the infrastructure of the world’s public conversation. Events break on Twitter, from massive and world-changing to the local data science meetup. Users exchange and shape their thoughts by forming communities with shared interests.

The Applied Research team thrives to understand, document and explain these phenomenons through rigorous data analysis in order to find disruptive growth opportunities in better serving our users.

We use machine learning, statistical modeling, data mining, time series modeling, and many other analytical techniques on the petabytes of data our users generate every month. We build prototypes and work with the product teams to perform experiments — all applied at the scale of Twitter.



What you’ll do

You will work as an integral part of our data science team to develop and implement models, algorithms, and systems that can be applied at scale to Twitter data. Examples of the kind of work you might do include building deep neural networks to classify Twitter users and content, large-scale graph clustering and matrix factorization, recommendation algorithms, or time-series models on user log data. You’ll work with both engineers and data scientists on the team and elsewhere at Twitter.


Who you are:

You probably have

  • Several years of experience working in machine learning
  • A strong interest and experience in machine learning, including deep learning, building classifiers, clustering in high dimension, pattern recognition algorithms, and recommender systems
  • Experience with large datasets and modern data processing systems like Hadoop, Spark, Hive, and Presto
  • Good communication skills, a pragmatic approach to problem solving, and a strong quantitative background
  • Some experience with software engineering best practices (e.g., unit testing, code reviews, design documentation)
  • Knowledgeable of core CS concepts such as data structures, algorithms, and optimization
  • Publications in top conferences is a plus (e.g., ICLR, NIPS, ICML, KDD)


Requirements

  • An advanced degree (masters, PhD) in machine learning or related field with coursework in machine learning or equivalent work experience
  • Strong software development experience (e.g., Scala, Java, C++, etc.)
  • Strong machine learning/data analysis experience (e.g., Python, R, Matlab, etc.)
  • Familiarity with one or more Deep Learning frameworks (e.g., TensorFlow, Torch, etc.)
  • 3+ years of work experience in machine learning, artificial intelligence, statistics, or related fields

Engineering Hiring Process

Step 1

Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.

Step 2

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.

Step 3

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.

Application

By applying you expressly make the following representations and warranties and give your consents as described below:
Twitter, Inc. collects your personal data for the purposes of managing Twitter, Inc.’s recruitment related activities as well as for organizational planning purposes globally. Consequently, Twitter, Inc. may use your personal data in relation to the evaluation and selection of applicants including for example setting up and conducting interviews and tests, evaluating and assessing the results thereto and as is otherwise needed in the recruitment processes including the final recruitment. 
Twitter, Inc. does not disclose your personal data to unauthorized third parties. However, as a global corporation consisting of multiple affiliated companies in various countries, Twitter, Inc. has international sites and Twitter, Inc. uses resources located throughout the world. Twitter, Inc. may from time to time also use third parties to act on Twitter, Inc.’s behalf. You agree to the fact that to the extent necessary your personal data may be transferred and/or disclosed to any company within Twitter, Inc. group of companies as well as to third parties acting on Twitter, Inc.’s behalf, including also transfers to servers and databases outside the country where you provided Twitter, Inc. with your personal data. Such transfers may include for example transfers and/or disclosures outside the European Economic Area and in the United States of America.

Personal Information

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