Machine Learning Engineer – Health ML – San Francisco, CA

Machine Learning Engineer – Health ML

The Health ML engineering team is responsible for building scalable detection systems that keep spam, manipulation, and abuse at bay. We use ML and relevance techniques to make Twitter safer and to limit the spread of misinformation on the platform. Our team works across the product to detect abusive and spammy users and content, increase action on bad actors, drive changes in user behavior, and detect and remediate accounts that are violating the terms of service on Twitter.

We develop, maintain, and contribute to several machine learning models and systems, including

  • Models that detect unwanted interactions
  • Models to prioritize human review of accounts violating Twitter’s policies to more quickly take action and limit their damage
  • Detection of bots that misuse the platform or spread misinformation
  • Detection of repeat abusive offenders who create new accounts after being suspended
  • Real-time rule engines and clustering systems to identify and action on clusters of bad actors at scale

Teams Who Are Hiring

Platform Manipulation Aiming to stop adversarial efforts to manipulate our platform & mitigate attempts to artificially amplify or suppress information or manipulate people’s experience on Twitter.

Civic Integrity Protect and promote the health of public conversation on Twitter, as it relates to a specific civic event or broader civic engagement.

Abusive Interactions Ensuring Twitter is a safe space for public conversation (safe from severe abusive interactions) to enable users’ healthy participation.

Misinformation Reducing creation and remediate consumption of misleading information in order to eliminate its potential harm to Twitter users.

What You’ll Do

Although you will work on cutting-edge problems, this position is not a pure research position. You will participate in the engineering life-cycle at Twitter, including designing distributed systems, writing production code and data pipelines, conducting code reviews and working alongside our infrastructure and reliability teams. You’ll apply data science, machine learning, and/or graph analysis techniques to a variety of modeling and relevance problems involving users, their social graph, their tweets, and their behavior.

 

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