Senior Technical Product Manager, Ads ML Platform

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .

Team Description:

The Ads Marketplace team is a strategic growth engine for Reddit Ads. Our mission is to democratize high-performance advertising by enabling brands to achieve world-class results with minimal friction. To achieve this, we need an incredibly robust, scalable, and state-of-the-art Machine Learning infrastructure. The Ads ML Platform team is at the core of this mission, tasked with building the foundation that powers all of our content understanding, ad targeting, and ad ranking models. We are empowering our ML engineers and data scientists to move faster and build smarter.

The Role:

As the Staff Product Manager for the Ads ML Platform, you will hold significant ownership over the infrastructure and tools that make our ads marketplace intelligent. You will define the vision and build the roadmap for a platform that enables unparalleled engineering velocity and supports the most modern ML architectures.

You will be the bridge between complex ML systems and business outcomes. Whether it's integrating generative AI to increase developer productivity, establishing unified model-serving infrastructure, or optimizing GPU utilization, your work will directly accelerate how quickly and effectively we can ship highly-performant ad products. If you are passionate about the intersection of platform engineering and state-of-the-art ML research, this is the role for you.

Responsibilities

• Define the Vision: Shape the long-term strategy and roadmap for Reddit ’s Ads ML platform, ensuring we are adopting cutting-edge technologies (including Generative AI and LLM workflows) to stay ahead of the curve.
• Accelerate Velocity: Build products and tooling that dramatically reduce friction for Machine Learning Engineers (MLEs) and Data Scientists, enabling them to train, deploy, and iterate on models faster than ever.
• Cross-Functional Leadership: Partner deeply with Engineering, Data Science, and Ads Product teams to understand their constraints, prioritize platform initiatives, and deliver scalable infrastructure.
• Drive Execution and Adoption: Own key performance indicators (KPIs) around platform reliability, latency, cost-efficiency, usage metrics, and developer productivity.
• Stay Cutting-Edge: Keep your finger on the pulse of the broader ML ecosystem. Read the latest research papers, understand emerging architectures, and determine how they can be practically applied to Reddit