Distinguished Engineer

Pinterest•Seattle, WA

1d•$280,148 - $576,774•Remote

About The Position

We’re looking for a Distinguished 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. 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.

Requirements

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 Distinguished 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 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.

Responsibilities

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.