Distinguished Engineer

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.

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 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 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.