Manager, Machine Learning, Topics / NLP

Manager, Machine Learning, Topics / NLP

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

The Position

Who We Are:

The Topic 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 building topical models for our content. These include tweets, spaces, and other forms of user generated content on our platform. We apply and advance state of the art machine learning techniques to invent new models and systems that can be used to help us understand the semantics of these content, and ultimately improve various Twitter experiences for our customers.

We operate at scale whilst ensuring fair and ethical use of our models and data.

What you will do: You will be managing a team of machine learning engineers (MLE), with a goal of building topic models to understand the content that is generated on Twitter. As a key leader of the organization, you will help influence and drive our roadmap to ensure that we are able to service the needs and demands of our customers. You will partner with peer teams and managers to help focus the team on the right set of problems and approaches. You will be responsible for the smooth operations of the team. You will be key to growing and guiding the careers of the MLEs on your team. 

Who you are: 

Leader and Coach. You are a leader and strong people manager looking to serve the team and achieve team goals. You are a strong source of engineering talent and are comfortable closing applicants for your team and business. You are a coach who hires, develops and retains good ML talent.

Competent Practitioner. You have a proven track record of delivering NLP systems. You have sound knowledge of state-of-the-art NLP models (in particular deep learning models) and are capable of applying them to real-world problems. You are comfortable with building production-grade software systems, and are up-to-date with software engineering best practices. You are able to provide tech guidance and help to your junior peers.

Strong Collaborator. You are a good communicator with excellent active listening and empathy skills. You collaborate well with teams with different backgrounds/expertise/functions.

Qualifications

Bachelor degree in Computer Science or Machine Learning related degree; or equivalent work experience in the field

1+ years of experience leading a team of 5+ engineers focused on machine learning products

2+ years NLP applied research experience, preferably experience applying NLP research to real-world problems in the industry

2+ years of experience building production NLP models, and deploying them to solve inference challenges at scale

Experience driving impact through cross-functional leadership

Exceptional written and verbal communication skills

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.

Understanding of cost of software development/tech debt and long-term maintenance

Familiarity with one or more deep learning software frameworks such as Tensorflow, PyTorch

Preferably publications in top conferences/journals including ACL, EMNLP, and NAACL

Company Description

Twitter is what’s happening and what people are talking about right now. For us, life's not about a job, it's about purpose. We believe real change starts with conversation. Here, your voice matters. Come as you are and together we'll do what's right (not what's easy) to serve the public conversation.

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