Sr. Staff Software Engineer, Product ML Infrastructure

Pinterest’s Product ML Infrastructure (PMLI) team enables fast, safe, and efficient delivery of AI/ML solutions across Ads and Core critical products. We build unified data, training, feature, and inference infrastructure; this role will set technical direction across model training and serving, with a focus on GPU efficiency and large-scale ranking systems.

What you’ll do:

• Set the technical vision and roadmap for model training and serving across PMLI, with reusable interfaces to data and feature infrastructure.
• Lead architectures for distributed training, fine-tuning, distillation, evaluation, and high-scale CPU/GPU inference.
• Improve efficiency across data loading, distributed execution, GPU kernels and memory, compilation, quantization, scheduling, and capacity.
• Build reliable, observable platforms with strong quality guarantees and training/serving consistency.
• Partner with Ads and Core AI/ML teams to productionize features and models safely at Pinterest scale.
• Drive cross-organizational architecture decisions, migrations, and operational standards; mentor senior engineers and raise the engineering bar.
• Use AI-assisted development and analysis to accelerate prototyping, performance diagnosis, and validation while maintaining rigorous correctness and data safeguards.

What we’re looking for:

• A track record of setting technical strategy and delivering company-wide infrastructure initiatives in ambiguous environments.
• Deep expertise in distributed ML systems, including production experience with both large-scale training and online inference.
• Strong GPU performance knowledge, such as profiling, distributed execution, kernel and memory optimization, compilation, or quantization.
• Experience with AI/ML modeling, recommender systems, Ads ranking, retrieval, feature platforms, or similarly demanding ML workloads.
• Strong systems programming and design skills in C++, Java, or Python.
• High ownership and sound judgment in reliability, security, cost, and operational excellence.
• Demonstrated ability to use AI to improve speed and critically evaluate AI-assisted work, with accountability for correctness, quality, and sensitive data.
• Bachelor’s degree in Computer Science, Engineering, a related field, or equivalent experience.

In-Office Requirement Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
• This role will need to be in the office for in-person collaboration 1–2 times per quarter and therefore needs to be within a commutable distance of our Palo Alto, CA or San Francisco, CA office.

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