Staff PM, Ads ML Platform — Remote

Reddit, Inc.; New York (NY); On-site; USD 217,000 - 303,900; Full time

Benefits offered by this job

100% remote opportunity

Competitive salary and equity options

Comprehensive health benefits (medical

Generous 401k matching

Flexible vacation policy

Paid parental leave (4+ months)

Family planning support

Paid volunteer time off

Job summary

Reddit, Inc. seeks a Staff Product Manager for the Ads ML Platform responsible for defining the vision and building the roadmap for a scalable ML infrastructure that powers our ads marketplace.

You will bridge ML systems and business outcomes, enable rapid training, deployment, and iteration, and collaborate across Engineering, Data Science, and Ads Product teams to deliver high-impact, low-friction tooling.

Qualifications

• 7+ years in product management on internal technical products, developer tools, or ML platforms.
• Analytical, technically fluent with ML lifecycle (training, inference, deployment, monitoring).
• Passion for ML/AI; keeps up with research and industry trends.
• Strong problem-solving; translates GPU scheduling and latency into roadmaps.
• Excellent communication; translates tech to business and vice versa.

Responsibilities

• Define the vision and roadmap for Reddit's Ads ML platform with cutting-edge tech.
• Build tooling to reduce friction for ML engineers and data scientists.
• Partner with Engineering, Data Science, and Ads teams to prioritize initiatives.
• Own KPIs for reliability, latency, cost-efficiency, and productivity.
• Stay on the frontier of ML to apply new architectures.
• Convert pain points into precise product requirements.

Skills

Product management

Data systems

ML lifecycle

GPU scheduling

Communication

Job description

Reddit, Inc. seeks a Staff Product Manager for the Ads ML Platform responsible for defining the vision and building the roadmap for a scalable ML infrastructure that powers our ads marketplace.

You will bridge ML systems and business outcomes, enable rapid training, deployment, and iteration, and collaborate across Engineering, Data Science, and Ads Product teams to deliver high-impact, low-friction tooling.