Machine Learning Engineer, Ads Auction; Ads Marketplace Quality

Staff Machine Learning Engineer, Ads Auction (Ads Marketplace Quality)

Remote - United States

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 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

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Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries:
You can apply to work remotely in any country in which we have a physical presence.

We’re evolving and continuing our mission to bring community, belonging, and empowerment to everyone in the world. Providing a delightful and relevant experience to our users applies to our Ads like all of our offerings, and we’re excited to build a product that is best‑in‑class for our users and advertisers. The year ahead is a busy one!

The Ads Marketplace Quality team is growing and we are looking for an experienced machine learning engineer and domain expert to be part of the journey of developing a world‑class marketplace and optimizing for users, advertisers and Reddit value.

In this role, you will be responsible for developing and executing a vision to improve our Ads Marketplace  will develop a deep understanding of our marketplace dynamics and identify areas of improvements by getting to the bottom of data, design, implement and ship algorithms to production that improve our ads marketplace efficiency. You will specialize in improving and optimizing our ads auction and pricing mechanism which will have a direct impact on up leveling the utility for both our advertiser and user values.

You will also have the opportunity to work on other org‑wide strategic initiatives such as supply optimization and ad relevance, where you will drive and execute on Reddit’s vision to transform Reddit into an advertising platform that shows the right ads to the right users at the right time in the right context.

As a Staff Machine Learning Engineer in the Ads Marketplace Quality team, you will be an industry technical leader with domain knowledge in ads marketplace dynamics, auction and pricing, you will research, formulate, and execute on our mission to build end‑to‑end algorithmic solutions and deliver values to all the three‑sided participants to our marketplace. You are expected to be part of the technical leadership at the both team and organization level, and will have the opportunity to contribute your expertise and shape the future of the ads marketplace at Reddit.

• Lead and oversee the strategy development, quarterly planning and day‑to‑day execution of initiatives related to ads marketplace, auction and pricing.
• Proactively further our understanding of marketplace dynamics and develop algorithms to improve the efficiency and effectiveness of our ads marketplace, auction and pricing.
• Oversee end‑to‑end ML workflows—from data ingestion and feature engineering to model training, evaluation, and deployment that optimizes the ads marketplace efficiency.
• Be a mentor, lead both junior and senior engineers in implementing technical designs and reviews. Fostering a culture of innovation, technical excellence, and knowledge sharing across the organization.
• Be a cross‑functional advocate for the team, collaborate with cross‑functional teams (e.g., product management, data science, PMM, Sales etc.) to innovate and build products.

• 8+ years of experience with industry‑level product development, with at least 5+ years focused on data‑driven, marketplace‑optimization problem space at scale.
• Strong knowledge of ads marketplace optimization. Demonstrated experience architecting ads marketplace design, improving and optimizing ads auction and pricing mechanisms.
• Solid understanding of large‑scale data processing, distributed computing, and data infrastructure…