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Applied Scientist - Safety ML

Twitch

San Francisco (CA)

On-site

USD 136,000 - 224,000

Full time

4 days ago
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Job summary

Join a leading company as an Applied Scientist focusing on safety through machine learning. You will tackle significant challenges around user and content safety, collaborating with a dedicated team to develop data-driven solutions. This role requires strong technical skills and a passion for community safety, offering competitive compensation and comprehensive benefits.

Benefits

Medical, Dental, Vision & Disability Insurance
401(k)
Maternity & Parental Leave
Flexible PTO
Amazon Employee Discount

Qualifications

  • 2+ years of experience building models in NLP, deep learning, or related area.
  • 2+ years of coding experience for production systems.
  • Expertise in ML libraries and cloud services like AWS.

Responsibilities

  • Develop ML products to combat harassment and illegal content.
  • Collaborate with teams to integrate models into production.
  • Continually learn new ML techniques.

Skills

Machine Learning
NLP
Deep Learning
Anomaly Detection
Bot Detection
Python
SQL

Education

PhD/MSc Degree in Computer Science, Mathematics, Statistics, Physics, Engineering

Tools

Pytorch
Tensorflow
AWS

Job description

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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.

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 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 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.
  • 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:


  • 2+ years of hands-on industry experience building models for NLP, deep learning, bot detection, anomaly detection or in another practical ML domain.
  • 2+ years experience writing high quality code to ship those models in production systems.
  • 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.). Familiarity with operating in AWS or similar cloud-computing services.


Bonus Points


  • PhD with a specialization in Machine Learning.
  • 1+ years of experience working in the safety or fraud prevention 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


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

Job ID: TW8832

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 https://www.twitch.tv/jobs/en/#learn-more. Applicants should apply via our internal or external career site.

US Pay Per Year

$136,000—$223,400 USD

Twitch is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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

Seniority level
  • Seniority level
    Not Applicable
Employment type
  • Employment type
    Full-time
Job function
  • Job function
    Research, Analyst, and Information Technology
  • Industries
    Technology, Information and Internet

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