Senior Staff Machine Learning Engineer, ML Understanding
New
R
Reddit, Inc.Machine learning
Remote - United StatesFull-TimeStaff
Salary$266,000 — $372,400 USD
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Job Details
- Experience
- At least 10 years experience building and scaling production-grade ML systems
- Required Skills
- Machine LearningMLOps
Requirements
- Have at least 10 years of experience building and scaling production-grade ML systems.
- Bring experience in user modeling, large-scale representation learning, or recommender systems.
- Understand mainstream user-understanding ML approaches, including representation learning, behavioral modeling, and user clustering.
- Have experience or strong intuition applying LLMs or foundation models to evolve existing systems.
- Demonstrate a track record of taking ambiguous, high-impact initiatives from concept to production.
- Consider data, training, evaluation, serving, and adoption as an end-to-end system.
- Partner effectively with product, infrastructure, and other ML teams and align multiple stakeholders.
- Navigate trade-offs across model quality, latency, cost, and safety in large-scale user-facing systems.
- Mentor senior engineers, lead design reviews, and establish practices for reliable, scalable ML systems.
Responsibilities
- Define the unified user-understanding framework and technical strategy, including how user representations are computed, stored, and exposed.
- Lead the design and implementation of large-scale user representation models, including sequence-based, multi-interest, and multi-task models.
- Apply LLMs and foundation models to user modeling, including dynamic profiles, intent inference, and semantic reasoning over user behavior.
- Partner with platform teams to build large-scale learning and serving components, including embedding storage and retrieval, feature pipelines, and APIs.
- Work with ML and ranking infrastructure teams to support low-latency serving, high availability, and MLOps integration.
- Partner with Feeds, Notifications, Search, and Ads teams to drive experimentation and adoption of user-understanding models.
- Measure end-to-end impact of models on product metrics.
- Mentor senior and staff engineers, lead design reviews, and guide technical decisions and engineering best practices.
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