About the company
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.
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.
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 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.