Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch onLinkedIn,Twitter and on ourBlog.
About the Position
Twitch enables content creators to live-stream content to their communities across the globe. Our suite of promotional products help creators, brands, and sponsors accelerate the growth and engagement of their communities. On the newly formed Promotions team, you’ll work with a talented, passionate, and customer obsessed team that will work on greenfield promotional products and features.
We are looking for passionate applied scientists who are excited to solve challenging and open-ended problems in the creation of promotion products. The core problems within our domain are to determine how many streams to promote, which streams to promote, where to place them, and how to price them. We anticipate the solutions for these problems to rely on unsupervised and supervised learning techniques to predict conversions, reinforcement learning for picking optimal ranking functions, causal modeling to measure long term viewer impact of paid promotions, and optimal allocation techniques (constrained optimization with local and global constraints). As one of the first applied scientists on the team, you’ll be embedded in a multi-disciplinary team of world-class engineers and scientists to build and run models, as well as the tooling/infrastructure necessary to manage and continuously improve them.
As the leader in this space, Twitch has a unique opportunity to invent promotional products in a live-streaming context. Our products will include innovative real-time experiences specific to Twitch. If you’re excited about being one of the earliest members of this team and having an outsize impact in an area that’s ripe for innovation, come work with us!
Own the complete lifecycle of ML models: training, building, evaluating, publishing, and deploying, etc
Collaborate with software engineers to build tools, infrastructure, and workflows to support core modeling work
Collaborate with data scientists and product managers to shape the product roadmap
Research, prototype, develop and productionize ML techniques that improve our ability to develop and sustain an efficient marketplace
Stay current with state-of-the-art ML research, know when to apply it to your work, and collaborate with other applied scientists in related domains and problems.
Graduate degree (MS or PhD) in mathematics, statistics, or a related field with specialization in machine learning
5+ years of hands-on experience in predictive modeling and analysis, and in deploying machine learning / deep learning models
3+ years of hands-on experience in programming languages such as Java and Python
Prior ML experience in search advertising, paid listings, or related areas
Deep knowledge in one or more of the following areas, with either published research or publically available code: predictive modeling, deep models for recommendations, collaborative filtering, constrained optimization, RL and multi-armed bandits, etc.
Demonstrated strong software development skills via work experience or submissions to open source projects
Familiarity with AWS services
Management experience, or interest in growing into Applied Science Manager roles
Medical, Dental, Vision & Disability Insurance
Maternity & Parental Leave
Amazon Employee Discount
Monthly Contribution & Discounts for Wellness Related Activities & Programs (e.g., gym memberships, off-site massages, etc.)
Breakfast, Lunch & Dinner Served Daily
Free Snacks & Beverages
We are an equal opportunity employer and value diversity at Twitch. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.