Staff Machine Learning Engineer, Ads Foundational Representations

About the Role

The Ads Foundational Representations (AFR) team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing semantic, contextual, and behavioral information. We work on building embeddings to understand content and users' interests based on content interactions.

As a Staff ML Engineer, you will set the technical direction of multiple pillars, leading cross-functional ML projects end-to-end from high-level business gap analysis to engineering execution. Roughly 50% of your time will be spent on technical leadership and mentorship, and 50% on hands-on modeling, data engineering, and automation.

Responsibilities

• Providing technical leadership and mentorship to MLEs in the team: driving designs and reviews, establishing best practices in analysis, modeling, and engineering.
• Working closely with team/org leadership developing technical strategy for content-based embeddings and relevance for Ads.
• Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models.
• Working with local and 3rd-party LLMs/VLMs: extracting representations, developing evaluation methodologies, prompt tuning, and fine-tuning large models to build state-of-the-art embeddings.
• Building data processing and inference pipelines for models.
• Qualitative and quantitative evaluation of features, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments.
• Ensuring reliability, scalability, and performance of ML systems by writing automated tests, monitoring performance, and implementing best practices for model management.
• Participating in modeling and code reviews.
• Collaborating with cross-functional teams to translate business requirements into technical solutions.

Qualifications

Required

• 7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models.
• Demonstrated Staff-level technical leadership: mentoring engineers, driving standards, and leading complex cross-functional projects without direct people-management authority.
• Excellent communication skills, both verbally and in writing.
• Strong track record of working on content-rich NLP/CV problems at scale and using embeddings to solve them.
• Established data-driven approach for ML system development.
• Familiarity with the Ads domain and/or Search/Recommender systems.
• Experience with mainstream DL frameworks: PyTorch or TensorFlow.

Preferred

• Experience with our stack (Python, PyTorch, Airflow, BigQuery, Ray, Kubernetes, Kafka, GCP).
• Technical leadership experience: mentoring junior engineers and leading complex projects.
• Hands-on experience with using, fine-tuning, or building LLMs.

Interview Process Note

In select roles and locations, interviews may be recorded, transcribed, and summarized by AI, with the opportunity to opt out prior to any scheduled interviews.