Staff Software Engineer, Ads ML Infrastructure

Staff Software Engineer, Ads ML Infrastructure

About Pinterest:

Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. In your role, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping Pinners make their lives better in the positive corner of the internet.

Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more. 

Pinterest is one of the fastest growing online advertising platforms. Continued success depends on the machine-learning systems, which crunch thousands of signals in a few hundred milliseconds, to identify the most relevant ads to show to pinners. You’ll join a small team with high impact, which designs high-performance and efficient ML systems, in order to power the most critical, revenue-generating algorithms and models at Pinterest.

Ads ML Infra team holds a mission of accelerating machine learning velocity and quality for Pinterest Ads by providing simple, efficient and performant infrastructure, which includes:

  • Ads ML Feature Systems – Streaming & batch feature engineering infrastructure, to efficient  feature governance systems and high quality signal for Pinterest ads.
  • Ads ML Serving Systems – Building highly efficient, scalable and performant ads online inference systems on top of most advanced technologies including GPU and model quantization.
  • Ads ML Training systems – Use the principles of data-centric AI to speed up developer velocity and tackle the most challenging problem in the online advertising industry – privacy preserve ML. 

What you’ll do:

  • Build ML system solutions (training, inference and feature infra) that directly power new machine learning models to uplevel Pinterest monetization business to 100X+ scale.
  • Tackle unique challenges in the online advertising industry including ML data privacy, conversion/clickthrough modelling systems and high performance ML training and serving.
  • Work closely with Ads quality teams, build ML ecosystem solutions and tools to improve Ads machine learning innovation velocity.
  • Partner with data and infrastructure teams, to up-level the deployment and ML monitoring tools for all Ads Serving engineers.

What we’re looking for:

  • BS (or higher) degree in Computer Science, or a related field.
  • 7+ years of relevant industry experience in leading the design of large scale & production ML infra systems.
  • Strong communicator and collaborative team player.
  • Expertise with at least one programming language (Java, C++, Python). 
  • Experience with building distributed systems or recommendation infrastructure
  • Experience with at least one ML dev framework (Tensorflow, Pytorch) 

US Applicants:

  • The minimum and maximum salary for this position is $186,700 to $311,200 in the US;
  • This position is eligible for equity; and
  • Information regarding the culture at Pinterest and benefits available for this position can be found at https://www.pinterestcareers.com/pinterest-life/.

* This compensation and benefits information is based on Pinterest’s good faith estimate as of the date of publication and may be modified in the future. The level of pay within the range will depend on a variety of job-related factors that may include location, travel, shift requirements, relevant prior experience and/or education, or particular skills and expertise.

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Our Commitment to Diversity:

At Pinterest, our mission is to bring everyone the inspiration to create a life they love—and that includes our employees. We’re taking on the most exciting challenges of our working lives, and we succeed with a team that represents an inclusive and diverse set of identities and backgrounds.

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