Sr. Staff Software Engineer, Product ML Infrastructure

AI in this role

fine-tuning

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

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.

US based applicants only$245,402—$429,454 USD

Our 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. By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.

How we rate this

Sr. Staff Software Engineer, Product ML Infrastructure at Pinterest rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Fine Tuning

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Fine Tuning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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