Job details

Staff Software Engineer, Core ML Foundation

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.

Creating a life you love also means finding a career that celebrates the unique perspectives and experiences that you bring. As you read through the expectations of the position, consider how your skills and experiences may complement the responsibilities of the role. We encourage you to think through your relevant and transferable skills from prior experiences.

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's mission is to inspire individuals to create a life they love through its visual discovery platform. We empower over 500 million monthly active users to explore and act on their passions, from home decor to travel planning and beyond. To achieve this, we are committed to leveraging state-of-the-art data processing and machine learning technologies to harness the full potential of our extensive content and user data.

Are you passionate about groundbreaking advancements in machine learning and eager to impact a platform used by over 500 million people every month? Pinterest is seeking a dynamic and seasoned Staff Engineer to join our Core ML Foundation team. This pivotal role is your chance to be at the cutting edge of modernizing and scaling up our machine learning infrastructure, ensuring efficient data processing and fostering rapid innovation across our recommendation and personalization systems.

As the tech lead, you will be instrumental in transforming our ML ecosystem—replacing legacy stack with advanced technologies like Pytorch, Spark, Iceberg, and GPU-based solutions. You'll lead efforts to scale up our ML training, serving, and data generation capabilities, and spearhead the development of feature storage solutions that drive both real-time and batch ML applications.

Imagine contributing to a platform where your innovations directly enhance user experiences and enable millions to discover new possibilities every day. This role offers more than just a job; it’s an opportunity to shape the future of visual discovery and recommendations at Pinterest.

What you'll do:

Modernize the ML ecosystem across Pinterest content recommendation infra with a unified, modern, and scalable ML stack with Pytorch, Spark, Iceberg, and GPU based solution.
Design and build scalable feature storage solutions to support real-time and batch ML applications.
Work with product and engineering teams to understand dynamic requirements, incorporating these into the development roadmap.
Partner with cross-functional teams to define problems, identify technical challenges, and develop innovative solutions.
Stay abreast of the latest advancements in ML infrastructure and apply them to enhance our systems.
Develop and implement strategies for efficient data ingestion, model training, and serving, ensuring scalability and reliability.
Provide guidance and mentorship to engineers, fostering an environment of technical excellence and continuous improvement.

What we're looking for:

BS (or higher) degree in Computer Science, or a related field.
8+ years of relevant industry experience in leading the design of large scale distributed and/or production ML infra systems.
Deep knowledge with at least one state-of-art programming language (Java, C++, Python).
In-depth knowledge of building distributed systems or recommendation infrastructure.
Familiarity with big data technologies such as Spark, Kafka, Flink, Ray and Iceberg.
Hands-on experience with at least one modeling framework (Pytorch or Tensorflow).
Hands-on experience with model / hardware accelerator libraries (Cuda, Quantization).
Experience with scalable model serving frameworks such as Ray-serve or Triton.
Experience in designing and implementing feature storage solutions for ML workflows.
Excellent communication and collaboration skills, with a team player mindset.

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

$160,520—$330,146 USD

Our Commitment to Diversity:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require an accommodation during the job application process, please notify accessibility@pinterest.com for support.