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Lead Engineer, Machine Learning

LVMH · 287999, Sephora

Hybrid Posted 4 days ago

About this role

Lead Engineer, Machine Learning Published on 05.11.2026 Sephora Tech Reference: 287999 Add to favorites Open Share Place of employment : San Francisco, United States Contrat type : Permanent Job Work mode : Full Time Apply POSITION PROFILE Position Lead Engineer, Machine Learning Profile Job ID: 287999 Location Name: CA-FSC SF Off (0174) Address: 350 Mission St, 20th Floor, San Francisco, CA 94105, United States (US) Job Type: Full Time Position Type: Regular Job Function: Information Technology Work Location: Hybrid-San Francisco Belong to Something Beautiful At Sephora, beauty is about feeling seen, valued, and empowered, individually and collectively. It is connecting deeply with others, celebrating diversity and inclusivity, unlocking your potential, and making a difference every day. Together, we belong to something beautiful

Your Role at Sephora: Ready for a career glow up? As a Lead Machine Learning Engineer , you'll be the driving force behind the architecture, engineering, and deployment of cutting-edge AI/ML systems at enterprise scale. The work you do will impact beauty, as you redefine how we inspire and connect with our customers — building the next generation of intelligent, AI-powered experiences across the beauty space. You'll lead a team that's united in beauty, supported by those who are equally passionate about pushing the boundaries of applied AI, engineering excellence, and real-world product impact

What You'll Do: Architect & Engineer Production-Grade AI/ML Systems. Design, build, and maintain scalable ML and Agentic AI systems using established engineering design patterns. Lead security-first and reliability-first practices, maintain deep domain expertise in ML systems and LLM infrastructure, and proactively anticipate future technical needs, scalability requirements, and cost implications

(20%) Own End-to-End ML Solutions. Engineer and own batch and real-time model serving, agentic pipelines, RAG systems, and LLMOps infrastructure. Build

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