13 часов назад
Senior Staff Machine Learning Engineer, ML Understanding
266 000 - 372 400$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Staff Machine Learning Engineer, ML Understanding (Machine Learning/LLM): Building Reddit’s unified user representation layer for personalization across Feeds, Search, Notifications, and Ads with an accent on embeddings, interest modeling, behavioral signals, and foundation models. Focus on designing scalable low-latency learning and serving systems, applying LLMs to dynamic user profiles and intent inference, and driving adoption across product and infrastructure teams.
Location: Remote - United States
Base salary: $266,000–$372,400 USD per year, plus potential equity and commission depending on the position.
Company
Reddit is a large-scale community platform where users submit, vote on, and discuss content across more than 100,000 active communities.
What you will do
- Define a unified user-understanding strategy covering embeddings, tags, attributes, and LLM-based user profiles.
- Lead the design and implementation of large-scale user representation and interest models for Feeds, Notifications, Search, and Ads.
- Apply LLMs and foundation models to dynamic user profiles, intent inference, semantic reasoning, and context-aware personalization.
- Build scalable storage, retrieval, feature pipelines, APIs, and serving components with low latency and high availability.
- Partner with product, infrastructure, ranking, and downstream ML teams to drive experimentation and measurable impact.
- Mentor senior and staff engineers, lead design reviews, and establish engineering best practices.
Requirements
- At least 10 years of experience building and scaling production-grade ML systems.
- Strong experience with user modeling, large-scale representation learning, recommender systems, or related ML approaches.
- Experience applying or evaluating LLMs and foundation models to evolve existing ML systems.
- Ability to design end-to-end systems spanning data, training, evaluation, serving, and adoption.
- Experience driving ambiguous, high-impact initiatives and aligning product, infrastructure, and ML stakeholders.
- Strong judgment across quality, latency, cost, reliability, and safety in large-scale user-facing systems.
Culture & Benefits
- Comprehensive healthcare benefits and income replacement programs.
- 401(k) with employer match.
- Global benefits covering workspace, professional development, caregiving, and family planning.
- Gender-affirming care and mental health and coaching benefits.
- Flexible vacation, paid volunteer time off, and generous paid parental leave.
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