Senior Machine Learning Engineer, Ads Content Understanding

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. com . 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.

Ads Content Understanding (ACU) owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for: The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources). Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics.

Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations. Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs. Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams.

We are looking for a Senior Machine Learning Engineer (IC4) who will act as a key contributor to the Content Understanding roadmap for the Monetization org. This is not a research scientist or pure DS role; success is defined by robust, shipped systems and monetization impact. The ideal candidate is a pragmatic engineer with strong software engineering fundamentals and solid ML intuition—not a pure research scientist.

, video), and drive practical ML solutions that deliver business impact.

Responsibilities

: Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable ML pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production. Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, design reviews, setting technical standards, and uplifting the team’s modeling and systems craft. Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices.

, reviews vs. recommendations vs. comparisons vs.

Q A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products. Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.

Required Qualifications

: 5+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads.