Related skills
cloud python deep learning distributed training embeddingsπ Description
- Architect and lead large-scale ML techniques.
- Define and execute ML strategy to boost personalization and recommendations.
- Lead research on scalable ML systems and real-time adaptation.
- Partner with ML infra to build distributed training across GPUs and cloud.
- Establish and optimize real-time serving for embeddings with low latency.
- Collaborate with Feed Ranking, Ads, Content Understanding, Core ML to integrate models.
π― Requirements
- 8+ years in ML engineering focusing on large-scale systems and personalization.
- Expertise in modern deep learning architectures, including sequence models and foundational models.
- Design, implement, and optimize scalable ML architectures: distributed training and real-time inference.
- Strong software engineering in Python and C++, with ML infrastructure and cloud pipelines.
- Experience with A/B testing, model evaluation frameworks, and real-time feedback loops.
- Excellent communication skills to present ML concepts to stakeholders.
π Benefits
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
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