About Twitch

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 Position 

Twitch is building the future of interactive entertainment. We are looking for passionate applied scientists who are excited to solve challenging and open-ended problems in the creation of recommendation products. As an applied scientist on Twitch’s Recommendations team, your work will help us better understand user’s preferences for different kinds of content, and you will see your work used to power discovery across Twitch. You will be developing next-generation recommendation models products using state of the art machine learning (ML) models with a world class engineering team. You will help ensure that creators and viewers on Twitch can build thriving communities, by making sure viewers find content that is relevant to them and that creators of all kinds get opportunities to be discovered.

At Twitch, which is part of Amazon, you’ll experience the benefits of working in a dynamic, entrepreneurial environment in the heart of San Francisco, while leveraging the resources of Amazon. You will be a member of the broader Twitch applied science community which includes world-class scientists across various disciplines.

You’ll find a Requirements section below. If you meet all these then we encourage you to apply. If you only meet some of them but think this role sounds like something you’d be great at, we encourage you to apply. If you meet just one of them but think you’ll bring something unique to the team, we encourage you to apply.

Responsibilities

  • Work closely with the Channel Affinity Model engineering team to build 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
  • Stay current with state-of-the-art ML research, and know when to apply it to your work
  • Collaborate with other applied scientists in related domains and problems

Requirements 

  • Work closely with the Recommendations engineering team to build algorithms that scale and pipelines that accelerate model development
  • Research ML techniques that improve our ability to match users to content
  • Write production-quality code implementing your ideas
  • Stay current with state-of-the-art ML research, and know when to apply it to your work
  • Collaborate with other applied scientists in related domains and problems

Bonus Points

  • Deep knowledge in ONE of the following areas, with either published research or publically available code:
    • Recommendation and personalization algorithms: Collaborative filtering, deep models for recommendations, RL and multi-armed bandits for recommendations, etc.
    • Natural Language Processing: Word/Sentence Embeddings, Topic Detection, Sentiment Analysis, Entity Extraction, etc.
  • Demonstrated strong software development skills via work experience or submissions to open source projects
  • Familiarity with AWS services

Perks

  • 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 

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.

 

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Voluntary Demographic Questions

Our mission at Twitch is to enable creators to make a living entertaining and educating their fans. We serve a diverse, global community and it's important that we have teams with a wide range of backgrounds, experiences and perspectives, in order to better serve our streamers and grow our business. All team members play a vital part in bringing our mission to life. At Twitch, we believe everyone has a role to play in creating an inclusive environment where everyone can thrive and grow.

In order to measure our effectiveness in recruiting a wide range of talent to Twitch, we invite all applicants to self-identify their gender, race and ethnicity, gender identity, sexual orientation, disability and military veteran status.  It’s our policy to provide equal employment opportunities to all applicants based solely on their qualifications. Your voluntary self-disclosures will be anonymized in reporting, and will not be used in any aspect of employment related decisions, nor shared with hiring managers. Declining to self-identify will not subject you to adverse treatment. Twitch does not discriminate on the basis of gender, gender identity or expression, sexual orientation, race/ethnicity, veteran or disability status, or any other protected group. 

Self-identification categories:

  • Gender: a person’s sex, as defined by their assigned sex at birth.
  • Gender Identity: a person's internal perception of their gender and how they label themselves (may or may not correspond to gender assigned at birth).
  • Race/Ethnicity: a person’s race (Asian, Black, Native American or Alaska Native, Native Hawaiian or Pacific Islander, White, Two or More Races) and whether they identify as Hispanic/Latinx.
  • Sexual Orientation: a person's sexual identity in relation to the gender to which they are attracted.
  • Disability: a person who has a physical or mental impairment which substantially, or occasionally, limits one or more of their major life activities.
  • Military Service: a person who has spent time serving in any branch of the military (may be retired or active).

 

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