Principal Engineer, Core - Pinner Journeys

Pinterest; United States; On-site; USD 210,000 - 270,000; Full time

Job summary

Pinterest is seeking a Principal Engineer to set the technical vision and lead foundational work across Homefeed, Search, and AI Assistant experiences. You will drive long-term architecture, influence product and leadership, and push for system health, reliability, and scalability.

This senior technical leader role requires deep expertise in large-scale retrieval, ranking, ML, and LLM-enabled applications, with a track record of cross-org impact and mentorship of engineers.

Qualifications

• 15+ years of experience in large-scale systems and/or ML.
• Proven track record as Principal Engineer, Architect, or equivalent.
• Deep expertise in retrieval/ranking, representation learning, or LLMs.

Responsibilities

• Define long-term strategy and architecture for Homefeed, Search, and AI Assistant.
• Drive multi-year roadmap for signals, features, and models across surfaces.
• Lead design and adoption of large-scale retrieval and ranking systems.
• Architect integration of LLMs with the discovery stack.
• Set direction for experimentation, measurement, and evaluation.
• Provide hands-on technical leadership on high-leverage projects and mentor staff.

Skills

Large-scale systems

Machine learning

Search & ranking

LLMs & generative AI

Cross-org leadership

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.