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.

Who We Are:

The Knowledge Graph ML Team will research, develop and deploy core content understanding modeling techniques to align twitter data (tweets, users, spaces, search queries, etc) against the knowledge graph taxonomy. It will also work to continuously augment the graph itself and increase its connectedness. The team will support Twitter product use cases requiring signals about entities, events, trends, topical concepts and other semantic elements of interest to our customers. The team will partner with Cortex Applied Research and NLPS to investigate new machine learning techniques for improving our services and ensuring our product offerings employ state-of-the-art technology. The technology will utilize a multi-modal approach which will leverage both NLU and computer vision technologies.

What you will do: You will be managing a team of machine learning engineers (MLE), with the goal of building out a connected graph in areas needed by various products across Twitter.  Applying tools and ML models to define new graph nodes and predict edges between nodes in the graph as directed by product needs.

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.

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

A few other things we value:

Challenge - We solve some of the industry’s hardest problems. Come to be challenged, learn, and thrive as an engineer.

Diversity - Diversity makes us a better organization and team. We value diverse backgrounds, ideas, and experiences.

Work, Life, Balance - We work hard, but we believe with hard work should come balance.