Staff Technical Product Manager, Ads ML Platform

Remote from: USA
Salary, yearly, USD: 217,000 - 303,900
Department: Product & Operations
Employment type: Full Time,
Job posted: 2 Jun 2026
Apply before: 2 Jul 2026
Experience level: Senior
Views / Applies: 9 / 1

About company

About Reddit

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Internet
2005

Actively Hiring

AI Summary

Reddit seeks a Staff Technical Product Manager for its Ads ML Platform team, which builds the infrastructure powering ad targeting, ranking, and content understanding. The role involves defining the vision and roadmap for ML tools, integrating generative AI, and improving developer productivity. The ideal candidate has 7+ years of PM experience with a focus on internal technical products, data/ML platforms, or ads. They must be deeply technical, passionate about ML, and able to translate complex constraints into product requirements. This is a high-impact role directly accelerating Reddit's advertising capabilities.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires a rare combination of deep technical expertise in ML infrastructure, strategic product vision, and cross-functional leadership, making it extremely challenging.

Salary Analysis

AI Insight The offered salary range of $217,000 - $303,900 is highly competitive for a Staff-level Product Manager role in the US market, especially considering the specialized focus on ML platforms. The median of $260,450 is above the typical market range for similar roles, reflecting the seniority and technical demands.

Key Skills

Product Management Machine Learning ML Platform Ads Technology Generative AI Cross-functional Leadership Technical Strategy Developer Tools Data Infrastructure Scalability

Cover Letter Sample

I am writing to express my strong interest in the Staff Technical Product Manager, Ads ML Platform position at Reddit. With over 7 years of experience in product management for developer tools and ML platforms, I am excited about the opportunity to shape the infrastructure that powers Reddit's advertising marketplace.

My background includes leading cross-functional teams to build scalable ML platforms, reducing model deployment time by 40% through unified serving infrastructure. I have a deep understanding of the ML lifecycle, from training to monitoring, and am passionate about leveraging generative AI to accelerate developer productivity.

I am particularly drawn to Reddit's mission of democratizing high-performance advertising and the challenge of building a state-of-the-art platform for a community-driven ecosystem. I look forward to the possibility of contributing to your team and driving innovation in ad technology.

Possible Interview Questions

Can you describe your experience building and managing ML platforms? What key metrics did you use to measure success?

I led the development of a unified model-serving platform that reduced inference latency by 30% and increased model deployment frequency by 50%. Success metrics included model deployment time, platform uptime, resource utilization, and developer satisfaction scores.

How do you prioritize features for an internal platform when multiple teams have competing needs?

I use a combination of data-driven impact analysis and stakeholder alignment. I conduct user research to quantify pain points, then map them to business outcomes like developer velocity or cost savings. I also establish a clear roadmap with transparent trade-offs and communicate regularly.

How would you integrate generative AI into an ML platform to improve developer productivity?

I would identify repetitive tasks such as feature engineering, code generation for model pipelines, and automated documentation. By integrating LLM-based tools, we could generate boilerplate code, suggest model architectures, and automate testing, reducing development time.

Describe a time you had to make a difficult trade-off between technical debt and new features. How did you decide?

At my previous role, we had to choose between refactoring our training infrastructure or adding support for new model types. I evaluated the long-term cost of debt versus short-term gains, and decided to allocate 20% of sprint capacity to refactoring while still delivering key features, ensuring sustainable velocity.

How do you stay current with ML research and apply it to product decisions?

I regularly read papers from conferences like NeurIPS and ICML, and follow industry blogs. I then run small experiments or proof-of-concepts to assess feasibility. For example, I identified a new attention mechanism that improved model performance by 15% and integrated it into our 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’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).

Perks and Benefits:

100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
Competitive salary and equity options
Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc)
Generous 401k matching
Flexible vacation policy
Paid parental leave (4+ months)
Family planning support
Paid volunteer time off

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Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$217,000—$303,900 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

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