Engineering Manager, Machine Learning - Ads Targeting

San Francisco, CA

Who we are

The team is a mix of systems engineers, machine learning engineers, and data scientists.  Our mission is to leverage state of the art machine learning and data science techniques to enable an advertiser to efficiently reach their audience on Twitter, in a way that protects the integrity of their brand.  This includes applying machine learning techniques to both user modeling and content modeling: examples include inferring user demographics and interests, predicting the probability a user will engage with an ad, and topic modeling for mixed-media containing text, image, and videos!  For every ad shown on Twitter, our prediction systems evaluate thousands of ad candidates behind the scene to find the best one. When executed successfully, we create aha! moments for our users & advertisers and add huge value to the Twitter business & revenue.


Who you are

If you have empathy for engineers, passion for machine learning, drive to make huge business impact, and enjoy working on exciting algorithmic as well as deep infrastructure issues, all at a really big scale - you will find this role liberating and challenging.  We’re looking for a technical, industry experienced engineering manager to join us to join this stellar team of passionate and talented engineers. The candidate must have experience building and leading teams with a machine learning and data science focus.


Responsibilities

  • Be responsible for the team’s technical strategy and roadmap, leading the team to build and maintain high-performance, scalable systems and create a world class Ads Targeting product
  • Work with Product Managers to add new features and lead the technical direction & architecture for the team
  • Mentor and guide direct reports to perform code reviews to ensure high quality of our code base, so engineers are able to be on call for systems owned by the team and are able to operate independently
  • Collaborate & coordinate with multiple teams for shipping new product features.
  • Perform data analysis to figure out opportunity sizing (& prioritization) for product features, OKRs and find usage patterns and create success metrics for team
  • Improve the reliability and efficiency of Twitter's core systems
  • Support Twitter’s internal APIs and user-facing products
  • Develop elegant solutions to complex problems
  • Mentor, guide and manage interns, junior engineers and senior engineers
  • Work on our hiring initiatives to recruit engineering talent



Hiring Process

Step 1

After you apply, a recruiter may reach out to you for an introductory call.

Step 2

If your background is a match for the role, you may phone interview with 1-2 people.

Step 3

If you continue through the process, you will come onsite 1-2 times to interview with a total of 5-10 people.

Application

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