Related skills
nlp machine learning distributed systems llms📋 Description
- Design, build, and operate ML systems in the messaging stack for latency and scalability.
- Write and review designs solving open-ended ML/product problems in production.
- Partner with ML, data science, and product teams to identify opportunities and criteria, linking offline performance to production impact.
- Collaborate with Messaging, Trust & Safety, Localization, and Platform teams on long-term solutions.
- Mentor and support career growth of individual contributors.
- Establish engineering standards for ML integration, including feature flagging, A/B testing, observability, and graceful degradation.
🎯 Requirements
- 9+ years of relevant engineering hands-on experience.
- Bachelors, Masters, or PhD in CS or related field.
- Demonstrated experience shipping ML-powered product features in production (model serving, feature pipelines, online/offline evaluation, monitoring).
- Exceptional architecture abilities for large-scale applications.
- Familiarity with NLP/NLU techniques and LLMs applied to messaging, conversational AI, or content understanding.
- Experience operating distributed, real-time systems at scale with high reliability requirements.
- Experience with ML infrastructure at scale (feature stores, model registries, online inference platforms).
🎁 Benefits
- Bonus eligibility and equity.
- Comprehensive benefits package.
- Employee Travel Credits.
- Remote-eligible role with US-based employment considerations.
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