Sr. Staff Software Engineer, ML Platform
Job Summary
Pinterest is seeking a Senior Staff Software Engineer to lead technical strategy across their ML Platform teams, focusing on enabling advanced model architectures, improving system efficiency, and increasing developer velocity. The role involves collaborating with modeling and infrastructure engineers, prototyping new technologies, and guiding ML application projects at scale. Candidates should have experience with production ML systems, distributed architectures, and GPU-based deep learning techniques. The position emphasizes mentorship, cross-team collaboration, and developing solutions for large-scale ML workflows.
Required Skills
Benefits
Job Description
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
The ML Platform team builds tools and infrastructure that powers 40+ ML & AI applications, including recommendations, ads, visual search, notifications, content understanding, and Trust & Safety. Our team consists of
- ML Training: Training compute platform (including distributed and GPU training), PyTorch-based training environment, model management & deployment.
- ML Serving: Online inference, including large-scale ranking of tens of millions of requests per second. GPU acceleration. ML feature/score monitoring.
- ML Data: Feature and training dataset management. Data governance tools (ownership, lineage, usage tracking, and monitoring) for 400+ signals owned by teams across the company.
We are seeking a Senior Staff Software Engineer to help drive technical strategy across these teams. Our long-term objectives include:
- Enable advanced model architectures - Language models, Multi-modal models, Large embeddings, Large user sequence models - increasingly large models present new challenges for training and serving
- Improve system efficiency - GPU efficiency and overall cost management often goes hand in hand with more sophisticated model architectures.
- Increase developer velocity - solve major bottlenecks in development of large-scale ML systems to speed up iterations of ML features and models.
What you’ll do:
- Tackle ambiguous problem areas by gathering understanding from modeling and infrastructure engineers across the company, proposing and aligning on generalized solutions, and driving the implementation with a team of platform engineers.
- Prototype, investigate, understand latest technologies from industry and academia and find opportunities to build and deploy them at our scale.
- Identify and collaborate with ML engineers to help drive forward top business-impacting ML application projects.
- Provide technical mentorship and guidance to junior engineers within the team.
What we’re looking for:
- In-depth experience with production ML use cases and systems at scale, including with distributed systems architectures, big data processing (e.g. Spark, Flink), and training.
- Understanding of modern deep learning techniques, performance optimizations and GPUs.
- Experience with, and workflow management.
- Understanding the needs for large ML teams collaborating: governing the lifecycle and ongoing quality of features, datasets, models, and tracking the dependencies / lineage.
- Experience in platform engineering - developing solutions for a user base of other engineers.
- 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.
Our Commitment to Inclusion:
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