Sr. 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 LinkedIn and X,  and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide 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 a Senior 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 lead high profile projects where 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, engineers, and product stakeholders 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 our Senior Applied Science Manager. This position is located in San Francisco, CA.

You Will:

• Build machine learning products to protect Twitch and its users from abusive behavior such as harassment, spam, and violent or illegal content.
• Propose, design, and oversee execution for high-impact projects that work backwards from customer problems to develop the right solution for the job. Know when to use a classical ML model versus 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.
• Help drive science culture on the team by staying up to date and experimenting with new techniques in ML, software engineering, and safety.

You Have:

• 6+ years of hands-on industry experience building models for NLP, deep learning, bot detection, anomaly detection or in another practical ML domain.
• 6+ years experience writing high quality code to ship those models in production systems.
• Experience owning projects that involve numerous scientists and engineers.
• Experience working with non-technical stakeholders.
• Proficiency with ML techniques and best practices for risk or abuse detection.
• PhD / MSc Degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or similar quantitative field OR equivalent hands on experience. 
• Expertise with: Python and SQL, modern open source ML libraries (Pytorch, Tensorflow, etc.), developing software in AWS or similar cloud-computing services.

Bonus Points

• PhD with a specialization in Machine Learning.
• 1+ years of experience working in the Trust and Safety domain (not necessarily as a scientist).
• Experience communicating with both technical and non-technical partners and stakeholders.
• 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. 

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

Job ID: TW8774

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