# Sr. Staff Machine Learning Engineer, Homefeed

**Company:** [Pinterest](https://hotfix.jobs/companies/pinterest)
**Location:** Seattle, WA, Palo Alto, CA, San Francisco, CA
**Role:** Engineering Management
**Salary:** $209k – $430k/yr
**Experience:** 8+ years
**Skills:** Artificial Intelligence, Machine Learning, LLMs, Agentic Systems, Personalization, User Understanding, AI Infrastructure, Model Integration, Orchestration, Generative AI, Evaluation Frameworks, System Reliability, Privacy, Security, Data Science
**Posted:** 2026-08-24

> Leads the engineering organization and technical strategy for Pinterest’s AI foundations, proactive experiences, and assistant capabilities. The role requires senior leadership experience managing managers, strong AI/platform depth, cross-functional execution, and a track record of building scalable, high-performing teams.

## Job Description

## Responsibilities
- Define and drive organizational and technical strategy for AI Foundations and Proactive Experiences, including LLM-powered systems, agentic workflows, orchestration, and agentic user experiences.
- Build and lead a high-performing engineering organization of senior engineers and technical leads across multiple workstreams.
- Partner with Product, Design, Research, and Data Science to shape roadmaps for proactive and assistive experiences.
- Lead foundational AI capabilities for context-aware, personalized, and anticipatory experiences, including model integration, user understanding, orchestration, safety, and evaluation.
- Drive a multi-year roadmap for reusable AI capabilities across product surfaces and use cases.
- Raise engineering standards for reliability, experimentation, privacy, security, operational health, and cost efficiency.
- Establish operating mechanisms for technical direction and delivery, including planning, design reviews, roadmap management, goal setting, and dependency management.
- Hire, retain, and develop talent while fostering an accountable, inclusive, high-performing engineering culture.
- Coach managers and senior individual contributors and develop the leadership bench.
- Partner with senior leadership to align investments, resolve tradeoffs, and focus on high-leverage opportunities.

## Requirements
- Significant experience leading engineering teams in AI/ML, personalization, intelligent product experiences, platform engineering, or consumer-facing AI systems at scale.
- Experience managing managers and senior technical leaders across complex, cross-functional problem spaces.
- Strong track record driving strategy and execution for large-scale technical organizations involving AI systems, platform capabilities, personalization, or generative AI.
- Experience with one or more of foundation model integration and LLM-powered systems, personalization and user understanding, agentic systems and orchestration, proactive or assistive experiences, or generative AI infrastructure, tooling, and evaluation.
- Ability to lead through ambiguity and turn early-stage opportunities into roadmaps, team structures, and measurable outcomes.
- Strong product and business judgment.
- Excellent partnership skills with Product Management, Design, Data Science, Research, and engineering leadership.
- Strong technical depth in architecture, platform design, model tradeoffs, and execution risks.
- Track record of building inclusive, high-performing engineering cultures and developing leaders.
- Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.

## Nice to Have
- Experience with global-scale consumer products, personalization, creator tools, assistants, content understanding, or intelligent recommendation experiences.
- Experience leading AI assistants, proactive recommendation systems, agentic workflows, or LLM-powered consumer experiences.
- Experience scaling organizations through foundation-model adoption, AI infrastructure modernization, or shared AI capabilities across product areas.

## Compensation and Benefits
- Base salary range: $208,592–$429,545.
- Eligible for equity.
- In-office collaboration is required 1–2 times per month.

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