San Francisco, CA, USA
12 days ago
Applied Scientist
About Us

Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.

We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on  and ,  and discover the projects we’re solving on our . Be sure to explore our  to learn how to ace our interview process.

About the Role

We are looking for applied scientists to solve challenging and open-ended problems in the domain of user and content safety. As an applied scientist on Twitch's Community team, you will use machine learning to develop data products tackling problems such as harassment, spam, and illegal content. You will use a wide toolbox of ML tools to handle multiple types of data, including user behavior, metadata, and user generated content such as text and video. You will collaborate with a team of passionate scientists and engineers to develop these models and put them into production, where they can help Twitch's creators and viewers succeed and build communities.

You will report to an Applied Science Manager. This position will be located in San Francisco.

You Will: Build machine learning products to protect Twitch and its users from abusive behavior such as harassment, spam, and violent or illegal content. Work backwards from customer problems to develop the right solution for the job, whether a classical ML model or a state-of-the-art one. Collaborate with Community Health's engineering and product management team to productionize your models into flexible data pipelines and ML-based services. Continue to learn and experiment with new techniques in ML, software engineering, or safety so that we can better help communities on Twitch grow and stay safe. You Have: MSc Degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or similar quantitative field OR 2+ years equivalent hands on experience. We welcome applicants with non-traditional backgrounds (e.g. bootcamps). Hands-on experience with predictive modeling and analysis to solve real-world problems. Proficiency in building models for NLP, deep learning, bot detection, anomaly detection or in another practical ML domain. Proficiency with Python; basic proficiency with SQL. Bonus Points Degree with a specialization in Machine Learning. Experience shipping your models to production. Familiarity with AWS or similar cloud-computing services. 1+ years of experience working in the safety or fraud prevention domain (not necessarily as a scientist). Familiarity with Twitch, its business, and its community. Perks Medical, Dental, Vision & Disability Insurance 401(k) Maternity & Parental Leave Flexible PTO Amazon Employee Discount

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. 

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

Twitch values your privacy. Please consult our , for information about how we collect, use, and disclose personal information of our candidates.

Job ID: TW8496

#LI-Remote #RemoteFriendly

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from our lowest geographic market up to our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain open until filled. For more information, please visit . Applicants should apply via our internal or external career site.

 

Remote US Pay Per Year$129,400—$212,800 USD
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