Machine Learning Software Engineer - Product Modeling - Cortex

Boston, MA

Who we are

Twitter users generate many terabytes of data every single day; Twitter engineers run hundreds of experiments; Twitter data scientists craft increasingly sophisticated models of users and content.

The  Applied Research team at Twitter works to measure and understand the satisfaction and motivations of our users.  Applied Research is part of the larger Analytics team at Twitter. From modeling individual user behavior to characterizing user populations, our work powers core systems at Twitter and helps inform product strategy. To develop a deep understanding of our users, we use machine learning, statistical modeling, data mining, time series modeling, and many other analytical techniques; we build prototypes; and we 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 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
  • An advanced degree (masters, PhD) in machine learning
  • Strong interest and experience in machine learning, including deep learning, building classifiers, natural language processing (NLP), 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


Requirements

  • Bachelors degree or higher in Computer Science or related field with coursework in machine learning (or equivalent work experience)
  • Strong software development experience (e.g., in Scala, Java, C++, etc.)
  • Strong machine learning/data analysis experience (e.g., in Python, R, Matlab, etc.)
  • 3+ years of educational or work experience in machine learning, artificial intelligence, statistics, or related fields


We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.


San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.



 

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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U.S. Equal Opportunity Employment Information  (Completion is Voluntary)

At Twitter, we have a bold aspiration to reach every person on the planet. We believe that goal is more attainable with a team that understands and represents different cultures and backgrounds and we are committed to an inclusive and diverse Twitter.

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Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

You can view the ‘EEO is the Law’ poster here.

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