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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’s Ads ML platform.
- Distill pain points, translate to requirements: Conduct regular user research with MLEs in Ranking, Creative Effectiveness and Content Understanding to convert pain points (e.g., slow backfills, limited training speed, no way to quickly share features across models) into precise product requirements. Validate the needs and ensure they are tied into a broader vision for the org.
Minimum Qualifications
- At least 7+ years of product management experience, with prior focus internal technical products, developer tools, data/ML platforms, and/or ads and content ranking.
- Deeply analytical and highly technical background; you are comfortable working in complex data systems and understanding the entire machine learning lifecycle (training, inference, deployment, monitoring).
- Genuine passion for machine learning and AI; you stay at the forefront of ML, enjoy reading ML research papers, stay informed on the latest industry trends, architectures, and capabilities.
- Exceptional problem-solving skills and the ability to translate highly technical constraints (e.g., GPU scheduling, latency budgets) into actionable product roadmaps.
- Strong communication skills; you can seamlessly translate technical requirements to business stakeholders and articulate business goals to engineering teams.
Preferred Qualifications
- Prior professional experience as a Machine Learning Engineer, Data Scientist, or Backend Software Engineer before transitioning into Product Management.
- Understanding of the Ad Tech ecosystem (bidding, ranking, targeting).
- Experience implementing or managing systems that support Generative AI/LLM workflows (Agentic automation, Prompt iteration, Fine-tuning, RAG).
