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Model Policy Manager in Seattle

18 active opportunities · Updated for October 2026

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Explore current model policy manager jobs in Seattle. Use filters to narrow by work mode, employment type, experience and date posted.

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Brex
📍 Seattle• Full-time• $280K – $350K/yr
14 days ago

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Product at Brex The Product team is at the forefront of Brex's mission to empower employees anywhere to make better financial decisions. With a deep understanding of the business, Product identifies, scopes out, and helps build the most impactful opportunities for Brex to tackle. We are responsible for aligning cross-functional teams — such as Engineering, Legal, Compliance, and Design — on key decisions. We set strategy and drive products from inception to launch, enabling Brex to grow rapidly and help our customers reach their full potential. What you’ll do As a Group Product Manager, you'll own a product area that sits at the center of Brex's highest-priority bets, setting the multi-quarter vision, making hard prioritization calls, and ensuring your team delivers outcomes that move company-level metrics, not just ship features. This means operating across several modes. Leading strategy, identifying where AI and automation can mean

aiaccountingfinance
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O
1mo ago

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. The Engineering Acceleration team builds products that multiply the effectiveness of OpenAI’s technical teams, helping engineers, researchers, and product teams understand complex systems, learn from what they ship, and operate reliably at scale. As AI changes how software is built, we have an opportunity to rethink engineering workflows from first principles. We’re creating tools and shared systems that turn complex data, experimentation, and technical workflows into clear decisions and useful action. About the Role In this role, you’ll lead design across two connected product areas: a real-time data exploration and observability experience for investigating large-scale system and product behavior, and an experimentation platform for safely launching changes, measuring their impact, and deciding whether to ramp, iterate, or roll back. This is more than a dashboard-design role. You’ll define the interaction models that take someone from a vague question or unexpected signal to a trustworthy answer and clear next step. You’ll work closely with engineers, researchers, data scientists, and product teams to understand the mechanics of their work and make dense technical systems coherent without flattening the details that matter. You’ll also help establish greater consistency across OpenAI’s enterprise and internal tools, developing durable patterns that support AI-native workflows and enable other designers to build more effectively. This role is based in our Seattle, WA or San Francisco, CA offices. We offer relocation assistance to new employees. In this role, you will: Lead end-to-end design for data-intensive products used by engineers, researchers, and product teams. Shape the complete learning loop: instrument, launch, observe, investigate, evaluate, decide, and iterate. Create clear, high-craft workflows for querying, filtering, comparison, drill-d

awsrestai
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O
OpenAI
📍 Seattle• Full-time• $293K – $325K/yr
1mo ago

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement ro

pythonjavavue
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