Senior Scientist - Recommendations

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What Twitch is looking for in applicants

About Us

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 on LinkedIn, Twitter and on our Blog.

About the Role

The Twitch service is growing at a rapid clip, connecting millions of creators with millions of viewers. Connecting the right viewers to the right creators helps build the community and strengthens the service. A large part of this discovery is guided by Machine Learning (ML) based recommendation systems. Twitch is looking for a Senior Applied Scientist to join our Recommendations team. You will work with other Applied Scientists and software engineers to develop next-generation recommendation systems using Deep Learning and machine learning (ML) techniques, and report to the manager of the recommendations team. You will develop models that may improve the state-of-the-art to help grow your team's impact and scope. You will work cross-team with product and program leadership, and will see your work used to power discovery products across Twitch. You will work towards helping Twitch viewers and content creators build thriving communities by helping viewers find relevant content and helping creators get discovered. Your work will ensure fairness in discovery of creators, and making sure viewers get healthy recommendations.

You Will:

  • Build ML algorithms that scale and pipelines that accelerate model development
  • Research, prototype, develop and productionize ML techniques that improve our ability to match users to content
  • Run experiments to validate impact and improve speed of iteration
  • Stay current with latest ML research, and know when to apply it to your work
  • Work with other applied scientists in related domains and problems
  • Publish outcomes in internal and external conferences

You Have:

  • Master's or Ph D in CS, Math, Stats or equivalent hands on experience
  • Knowledge of Deep Learning algorithms and experience using Deep Learning libraries such as TensorFlow, PyTorch, MxNet, etc.
  • 3+ years experience in a general purpose programming language: Python, Go, C/C++, Python, Java, etc

Bonus Points

  • Knowledge in ONE of the following areas, with either published research or publicly available code:
  • Recommendation and personalization algorithms: Collaborative filtering, deep models for recommendations, RL and multi-armed bandits for recommendations, causal inference and learning from biased data
  • Apply multiple forms of data: Self-supervised learning, multi-task learning, transfer learning.
  • Architectures related to sequential or time-series data: Attention/transformers, recurrence, convolutions.
  • Anything you believe is related to the recommendation problem on industry-scale data.
  • Familiarity with AWS services


  • Medical, Dental, Vision & Disability Insurance
  • 401(k), Maternity & Parental Leave
  • Flexible PTO
  • Commuter Benefits
  • 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 

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

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, gender identity, sexual orientation, age, marital status, veteran status, or disability status, or other legally protected status.

Want some tips on how to get an interview at Twitch?

What is Twitch looking for?
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