Staff Software Engineer, Capacity Engineering
San Francisco, CA, US; Remote, CA, US
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 is seeking a Staff Software Engineer, Capacity Engineering focused on managing and optimizing the ML infrastructure. The team is responsible for efficiently managing one of the largest-scale cloud-native infrastructures in the world.
This role is highly impactful, as efficiency is an ongoing strategic priority for Pinterest. The role has direct visibility across Pinterest Engineering and with Engineering and company leadership. The team is looking for a candidate with a strong background in ML Infrastructure focusing on efficiency and optimization.
What you’ll do
- Manage the ML hardware capacity that powers the models running at Pinterest
- Improve the efficiency of ML Infrastructure at Pinterest
- Build develop and mature profiling and optimization capabilities for ML Infrastructure at Pinterest scale
- Collaborate with ML Platform, Infrastructure Engineering and SRE teams in their mission to deliver highly available, resilient, secure and efficient ML foundations for Pinterest’s tech stack
What we’re looking for:
- Deep understanding of GPU Architectures, Pytorch, etc.
- Deep understanding of supporting parts of ML software stack like Scheduling, Data and Storage
- Hands on experience with shared platforms like Kubernetes
- Strong technical and performance engineering skills to collaborate with stakeholders on complex and ambiguous technical challenges
- Experience building and managing highly available distributed applications at scale
- Proficiency in software development languages such as Java, Python and C++
- Excellent skills in communicating complex technical issues
- Understanding of ML Models, Kernels and optimization opportunities
- Hands-on experience with large, cloud-native multi-tenant platforms at Internet scale
- Experience with AWS or similar cloud environments
- Deep understanding of infrastructure capacity and performance
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
In-Office Requirement Statement:
We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
- This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
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$170,371—$350,763 USDOur Commitment to Inclusion:
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 a medical or religious accommodation during the job application process, please complete this form for support. ApplyJob Profile
In-office requirement In-office requirement 1-2 times/quarter Not eligible for relocation Not eligible for relocation assistance US based applicants only
Benefits/PerksEquity Flexible work model Inclusive workplace In-person collaboration opportunities Remote-first company
Tasks- Build profiling and optimization capabilities
- Collaborate
- Collaborate with stakeholders
- Collaborate with teams
- Improve efficiency of ml infrastructure
- Manage ml hardware capacity
AWS C++ Cloud environments Cloud-native platforms Collaboration Distributed Applications Engineering Equity GPU GPU Architectures Inclusion Infrastructure Java Kubernetes Leadership ML ML Infrastructure Optimization Performance engineering Python PyTorch Scheduling Software Development SRE Storage
EducationBachelor Bachelor's degree in Computer Science Bachelor's degree in engineering Bachelor’s Degree in Related Field Computer Science Degree in Computer Science Engineering Equivalent experience Legal ML Related Field
Certifications TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9