Ads Conversion Modeling, Machine Learning Engineering Manager

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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .

Reddit’s lower funnel business is rapidly growing and pushing the heavy ranking web conversion models towards state-of-the-art is critical for continued growth. The Conversion modeling Team plays a pivotal role in developing and maintaining machine learning models that drive user conversions from Reddit Ads, with a special focus on predictive modeling around interactions like purchase, signup, add to cart, and other lower funnel user actions.

As we expand our machine learning infrastructure and incorporate new engagement signals, we are looking for a skilled Engineering Manager who can lead this critical team. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders.

We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S.

Target Skills and Expertise

The Engineering Manager (EM) will be responsible for defining the team’s vision, setting strategic direction, and executing a technical roadmap for conversion modeling at Reddit. This involves:

Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling.

ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch).

End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models.

Data Pipelines: Experience orchestrating large-scale data generation and processing pipelines.

Ads domain Experience: Experience in interaction of ranking model with rest of Ads systems like bidding, auction, retrieval etc

Ads Modeling (Preferred): Background in ads modeling or familiarity with engagement prediction models in the ads domain is beneficial.

Role responsibilities:

The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:

People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.

Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.

Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.

Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.

Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.

Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.

Required qualifications:

At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well

Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems. Proven ability in training, evaluating, and deploying large-scale models.

Technical Domain Knowledge: Experience with Ads conversion modeling, ranking (heavy ranker experience) & recommendations experience is required.