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. 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 . About the role: We’re looking for a Principal Engineer to set the technical vision and lead foundational work across Homefeed, Search, and our emerging AI Assistant experiences at Pinterest. This role sits at the intersection of relevance, ranking, retrieval, and generative AI, and will shape how hundreds of millions of Pinners discover and act on inspiration every day. You will operate as a cross-cutting technical leader: defining long-term architecture, raising the bar on ML and systems excellence, and partnering closely with product and executive leadership to drive step‑function improvements in engagement, quality, and creator value. What you’ll do: Define the long-term technical strategy and architecture for Homefeed, Search, and AI Assistant, including retrieval, ranking, personalization, and generative experiences. Drive a multi‑year roadmap for unifying signals, features, and models across surfaces to deliver a coherent, high-quality discovery experience. Lead the design and adoption of large-scale retrieval and ranking systems (e.g., multi-stage retrieval, representation learning, multi-objective optimization) that materially improve relevance and monetization. Architect how LLMs and foundation models integrate with our core discovery stack (e.g., query understanding, intent modeling, content understanding, conversation orchestration, safety/guardrails). Set technical direction for experimentation, measurement, and evaluation frameworks, including offline metrics, online experimentation, and causal inference for discovery and generative use cases. Provide hands-on technical leadership on a small number of high-leverage projects: design critical components, review designs/PRs, de-risk complex launches, and mentor senior engineers and staff+ TLs. Partner deeply with Product, Data Science, Research, and Design to frame the right problems, translate product bets into robust technical plans, and ensure we are solving for long-term platform health, not just short-term metrics. Raise the bar for engineering excellence: reliability, performance, security/privacy, cost efficiency, and operational health of large-scale ML systems. Represent Pinterest externally for these domains (e.g., talks, publications, partnerships) and help attract and grow top talent. You will report into Pinterest’s Core Engineering leadership and work horizontally across multiple product and platform teams responsible for Homefeed, Search, and AI Assistant. You will spend a meaningful portion of your time on hands-on technical work (design, reviews, prototyping) while also driving long-term strategy, standards, and alignment across organizations. You will be measured on durable technical impact: system-level improvements, model and product outcomes, reduction in complexity and operational risk, and the growth of leaders and capabilities around you. What we’re looking for: 15+ years of industry experience in large-scale systems and/or machine learning, with a track record of impact in search, recommendations, feeds, or conversational AI. Proven experience as a Principal Engineer, Architect, or equivalent senior technical leader driving cross‑org technical strategy and execution. Deep expertise in at least two of the following, and strong familiarity with the others: Large-scale retrieval and ranking (e.g., learning-to-rank, multi-task and multi-objective optimization, bandits, RL for recommendations). Representation learning (e.g., embeddings, multi-modal models, dense and sparse retrieval). Search systems (indexing, query understanding, relevance tuning, latency/throughput optimization). Large language models and generative AI (prompting, fine-tuning, RAG, agents, safety/guardrails, evaluation). Demonstrated ability to define and drive multi-year architectural transformations at scale (e.g., re-architecting a core ranking stack, unifying feature platforms, evolving legacy systems to modern ML platforms). Strong product intuition and experience partnering with PM/Design/Data Science on ambiguous, 0→1 and 1→N product bets. Exceptional communication skills: able to crisply articulate strategy, tradeoffs, and technical direction to executives, peers, and broad engineering audiences. Passion for mentoring and growing senior/staff engineers; history of building strong engineering cultures and communities of practice. Bachelor’s degree in computer science, a related field or equivalent experience. Nice to have: Prior experience in consumer discovery products at global scale (e.g., feeds, search, recommendations, marketplaces, or assistants). Experience building or integrating AI assistants or agentic workflows into consumer experiences. 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. Some teams will need you to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. While other teams will need you to be in the office for in-person collaboration 1 times per week and therefore needs to be in a commutable distance from one of the following offices, [SF, Palo Alto, Seattle]. #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 $242,634 — $449,541 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.

Requirements

Must-haves

Define the long-term technical strategy and architecture for Homefeed, Search, and AI Assistant, including retrieval, ranking, personalization, and generative experiences.
Drive a multi‑year roadmap for unifying signals, features, and models across surfaces to deliver a coherent, high-quality discovery experience.
Lead the design and adoption of large-scale retrieval and ranking systems (e.g., multi-stage retrieval, representation learning, multi-objective optimization) that materially improve relevance and monetization.
Architect how LLMs and foundation models integrate with our core discovery stack (e.g., query understanding, intent modeling, content understanding, conversation orchestration, safety/guardrails).
Set technical direction for experimentation, measurement, and evaluation frameworks, including offline metrics, online experimentation, and causal inference for discovery and generative use cases.
Provide hands-on technical leadership on a small number of high-leverage projects: design critical components, review designs/PRs, de-risk complex launches, and mentor senior engineers and staff+ TLs.
Raise the bar for engineering excellence: reliability, performance, security/privacy, cost efficiency, and operational health of large-scale ML systems.
Represent Pinterest externally for these domains (e.g., talks, publications, partnerships) and help attract and grow top talent.
You will report into Pinterest’s Core Engineering leadership and work horizontally across multiple product and platform teams responsible for Homefeed, Search, and AI Assistant.
You will spend a meaningful portion of your time on hands-on technical work (design, reviews, prototyping) while also driving long-term strategy, standards, and alignment across organizations.
You will be measured on durable technical impact: system-level improvements, model and product outcomes, reduction in complexity and operational risk, and the growth of leaders and capabilities around you.
15+ years of industry experience in large-scale systems and/or machine learning, with a track record of impact in search, recommendations, feeds, or conversational AI.
Proven experience as a Principal Engineer, Architect, or equivalent senior technical leader driving cross‑org technical strategy and execution.
Deep expertise in at least two of the following, and strong familiarity with the others:
Large-scale retrieval and ranking (e.g., learning-to-rank, multi-task and multi-objective optimization, bandits, RL for recommendations).
Representation learning (e.g., embeddings, multi-modal models, dense and sparse retrieval).
Search systems (indexing, query understanding, relevance tuning, latency/throughput optimization).
Large language models and generative AI (prompting, fine-tuning, RAG, agents, safety/guardrails, evaluation).
Demonstrated ability to define and drive multi-year architectural transformations at scale (e.g., re-architecting a core ranking stack, unifying feature platforms, evolving legacy systems to modern ML platforms).
Strong product intuition and experience partnering with PM/Design/Data Science on ambiguous, 0→1 and 1→N product bets.
Exceptional communication skills: able to crisply articulate strategy, tradeoffs, and technical direction to executives, peers, and broad engineering audiences.
Passion for mentoring and growing senior/staff engineers; history of building strong engineering cultures and communities of practice.

Nice-to-haves

Prior experience in consumer discovery products at global scale (e.g., feeds, search, recommendations, marketplaces, or assistants).
Experience building or integrating AI assistants or agentic workflows into consumer experiences.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learning

Platform: greenhouse
Effort: quick

Benefits

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Vision