Staff Machine Learning Engineer, Retrieval & Targeting

Reddit is a community of communities. 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. Team Description: The Ads Retrieval ML team builds the machine learning systems that identify relevant advertising candidates for Reddit users. Our work combines representation learning, candidate generation, nearest-neighbor search, behavioral and contextual signals, and rigorous offline and online experimentation.

We are looking for a Staff Machine Learning Engineer to provide technical leadership for the Retrieval and Targeting ML team. You will lead the design and evolution of retrieval models and modeling practices that improve relevance, advertiser outcomes, and user experience at Reddit scale. This is an applied ML role centered on retrieval modeling and end-to-end product impact. You will be expected to stay close to the technical details—from data and objective design through model development, evaluation, experimentation, and launch—while setting direction for other engineers.

Define the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and ads stakeholders.
Apply modern approaches such as two-tower architectures, representation learning, embeddings, sequence models, graph-based methods, and other deep learning techniques when they create meaningful product value.
Work with approximate nearest-neighbor and vector retrieval systems, reasoning about recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs.
Lead offline analysis and online experiments, interpret ambiguous results, and translate findings into the next modeling iteration.
Partner with downstream ranking, ads platform, auction, measurement, and product teams to ensure retrieval models integrate effectively into the full ads funnel.
Write design documents, review code and model changes, and raise the quality bar for modeling, testing, observability, and production ownership.
Mentor ML engineers and help grow the team’s expertise in retrieval, recommendation, and representation learning.
7+ years of industry experience, including substantial experience building and shipping applied ML products.
~ Deep experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.
~ Demonstrated ownership of ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
~ Experience working with large-scale behavioral, contextual, or content datasets and complex feature pipelines.
~ Strong software engineering fundamentals and the ability to write clear, reliable, maintainable production code.
~ Technical leadership experience: setting direction, leading complex projects, influencing partner teams, and mentoring other engineers.
~ Experience with ads retrieval, ads ranking, ad targeting, ad serving, recommendation, search relevance, or marketplace optimization
Experience modeling user, content, campaign, or ad interactions with sequential, graph, or multimodal signals
Experience connecting retrieval improvements to downstream ranking, auction, conversion, revenue, or user-experience outcomes
Publications, patents, or industry contributions in applied ML or ranking systems
RNNs, Transformers)
100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
~ Flexible Vacation & Paid Volunteer Time Off
~ 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. based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. 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.
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Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.

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