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.
Staff Machine Learning Engineer, Applied Science
Pinterest Labs is a group dedicated to using machine learning to bring inspiration to everyone. Tackling some of the most challenging problems in ML and AI, Labs solves the problem of discovery online and doing it in an inspiring and inclusive way.
In this role, you'll work on tackling new challenges in machine learning and artificial intelligence along with a world-class team of research scientists, and machine learning engineers. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: computer vision, graph neural network, natural language processing (NLP), inclusive AI, reinforcement learning, user modeling, and recommender systems.
What you’ll do:
- Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
- Collect, analyze, and synthesize findings from data and build intelligent data-driven model
- Write clean, efficient, and sustainable code
- Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search
- Scope and independently solve moderately complex problems
What we’re looking for:
- MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field
- 6+ years of industry experience
- Experience in machine learning/information retrieval/ recommendation systems
- Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
- Experience in research and in solving analytical problems
- Cross-functional collaborator and strong communicator
- Comfortable solving ambiguous problems and adapting to a dynamic environment
This position is not eligible for relocation assistance.
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.
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, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic under federal, state, or local law. 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 email@example.com for support.