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.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
Sr. Staff Software Engineer, Product ML Infrastructure
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.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
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.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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.
#LI-REMOTE
#LI-AG8
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:
Skills Required
- Track record of setting technical strategy and delivering company-wide infrastructure initiatives in ambiguous environments
- Deep expertise in distributed machine learning systems, including production experience with large-scale training and online inference
- Strong GPU performance knowledge, including 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 machine learning workloads
- Strong systems programming and design skills in C++, Java, or Python
- High ownership and sound judgment in reliability, security, cost, and operational excellence
- Ability to use AI effectively while evaluating AI-assisted work for correctness, quality, and sensitive-data safeguards
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience
- Ability to work within a commutable distance of Pinterest's Palo Alto or San Francisco office
Pinterest Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Pinterest and has not been reviewed or approved by Pinterest.
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Fair & Transparent Compensation — Compensation is considered competitive in core technical roles, with clearly defined base, bonus, and RSU components. Vesting schedules and pay elements are articulated clearly, supporting visibility into total rewards.
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Parental & Family Support — Policies include substantial paid parental leave globally alongside fertility and family‑building benefits, adoption assistance, and dedicated caregiver supports. Communications also highlight a phased return‑to‑work approach.
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Flexible Benefits — PinFlex enables role‑dependent hybrid/remote work with home‑office, connectivity, and commuter support, plus the option to work internationally for a limited period with approval. Time away is reinforced by a paid company shutdown and generous vacation framing.
Pinterest Insights
What We Do
Pinterest is the visual inspiration platform people around the world use to shop products personalized to their taste, find ideas to do offline and discover the most inspiring creators. Today, more than 460 million people come to the platform every month to explore and experience billions of ideas that have been saved. We’re proud to help people to discover and do what they love.









