Job Twitter: Engineering Manager – Ads Targeting & Modeling

Engineering Manager – Ads Targeting&Modeling

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 managing teams with a machine learning and data science focus.

 

Responsibilities

  • Mentor the professional development of each direct report through personal and performance management.
  • Be an aggressive source of engineering talent and be comfortable closing candidates.
  • Give engineers the tools, confidence, and motivation to make decisions independently that lead to the recognition of your engineers and the team.
  • Initiate cross-functional collaboration with Product, Research, Design, and other engineers in order to identify and implement improvements to Twitter’s ads stack using machine learning techniques.
  • Ensure the team fully understands the goals and objectives of Twitter as a company and how their work fits into the bigger picture.
  • Be responsible for the team’s technical strategy and roadmap – creating success metrics in close collaboration with other Engineering and Product Managers.

Qualifications

  • Previously managed a team of 5-10 engineers and has 1+ years of management experience. Experience with building products, taking them to the market and iterating and improving them over time.
  • Skilled in the application of machine learning to real world business use-cases.
  • Familiarity with basic fundamentals of probability theory and statistics.
  • B.S. or higher in Computer Science and a strong computer science foundation with a prior track record of excellence as an engineer.
  • Experience with software engineering best practices (e.g. unit testing, code reviews, design documentation). Disciplined approach to testing and quality assurance.
  • Bring a strong perspective that drives change and motivates engineers to develop simple solutions to complex problems.
  • Work with tech leads and senior engineers to gather product requirements, gut checks new feature proposals and large product improvements.

We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran, genetic information, marital status or any other legally protected status.

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

Engineering Hiring Process

Step 1

Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.

Step 2

If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.

Step 3

If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.


 we will review with hiring manager from Twitter.

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