Staff Applied ML Engineer (NLP)

Staff Applied ML Engineer (NLP)

This job has closed but is shown for context on data science work at Twitter.

Job description

Who We Are:

The Natural Language Processing (NLP) Signals team is part of Cortex, the central machine learning organization at Twitter. Cortex’s mission is to empower internal teams to efficiently leverage machine learning by providing platform, modeling, and research expertise while advancing the ML technologies within Twitter.

We tackle Twitter-specific challenges in the NLP domain such as the real-time, ever-changing nature of our data and limited context. We apply and advance state of the art natural language processing techniques to invent new models and systems that can be used to improve various Twitter experiences for our customers.

We encourage publishing papers while focusing on solving real-world problems that improve Twitter for our customers. We operate at scale whilst ensuring fair and ethical use of our models and data.

What you will do:

Apply your NLP expertise to propose and develop models and solutions that improve our ML-driven products. Devise models and algorithms and guide engineering to develop scalable solutions that can work in real-time with large amounts of data. Help us develop novel solutions, and unlock new directions. You’ll collaborate with product teams, mentor them on best practices for modern NLP, and keep the wider team informed on the state of the art. In addition, you will be in a strategic position to influence future roadmaps for NLP-driven products. You will engage with the research community via publications, workshops, and tutorials.


Who you are:

You have an in-depth knowledge and research experience in NLP. You are passionate about state-of-the-art technologies and are excited by the application of theory to real-world problems. You keep up to date with the latest developments in the field and look for ways to apply them to your current work/role.


  • Post-graduate or Ph.D. in Computer Science or Machine Learning related degree with a focus on NLP; or equivalent work experience in the field
  • 5+ years NLP research experience 
  • Experience with applying NLP models to live production systems 
  • Good theoretical grounding in core machine learning concepts and techniques
  • Ability to perform comprehensive literature reviews and provide critical feedback on state-of-the-art solutions and how they may fit different operating constraints
  • Experience with a number of ML techniques and frameworks, e.g., data discretization, normalization, sampling, linear regression, decision trees, SVMs, deep neural networks, etc.
  • Familiarity with one or more DL software frameworks such as Tensorflow, PyTorch
  • Backend development experience with a strong interest in work involving data pipelines, distributed systems, performance analysis, and/or large-scale data processing (ideally, in Java)
  • Experience with software engineering practices (e.g. unit testing, code reviews, design documentation)
  • Experience with large-scale systems and data, e.g. Hadoop, distributed systems
  • Work closely with consumer teams to build solutions that deliver impactful projects

Nice to haves:

  • Publications in top conferences/journals such as EMNLP, ACL, COLING, TACL, CoNLL, NeurIPs, ICML

Additional information

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, genetic information, marital status or any other 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.

This job has closed but is shown for context on data science work at Twitter.
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