Lead Machine Learning Engineer

Company Overview:

At Sephora we inspire our customers, empower our teams, and help them become the best versions of themselves. We create an environment where people are valued, and differences are celebrated. Every day, our teams across the world bring to life our purpose: to expand the way the world sees beauty by empowering the Extra Ordinary in each of us. We are united by a common goal - to reimagine the future of beauty.

The Opportunity:

Technology

Our technology team works fast and smart. With San Francisco as our home, we take bringing new tech to market seriously, developing the latest in mobile technologies, scalable architecture, and the coolest in-store client experience. We love what we do and we have fun doing it. The Technology group is comprised of motivated self-starters and true team players that are absolutely integral to the growth of Sephora and our future success.

Your role at Sephora...

This is an opportunity for a Lead Machine Learning Engineer to come in and drive AI/ML initiatives for the enterprise. Sephora continues to inspire our loyal customers in beauty space, and AI/ML is redefining the way we inspire our customers.

Some exciting initiatives in action:

• Generative AI use cases to help our customers discover products by developing AI agents

• Adopting reinforcement learning for hyper personalization

• Building RAG based knowledge bases for AI agents

• Model Context Protocol (MCP) Enablement to accelerate AI adoption

As a Lead Machine Learning Engineer, you will operationalize innovative AI/ML solutions and work alongside other team members like Product Manager, Enterprise Architect, ML Engineers, Data scientists and Business to architect, design, build and productionalize AI/ML models. You will be also responsible for integrating AI/ML solutions into operational products. This hands-on technical role demands excellent Data Science, ML engineering and ML ops/LLM Ops knowledge and can demonstrate best practices in the industry.

Come be a part of a team that is starting this new journey.

We are looking for someone who is a technology-agnostic polymath—committed to a lifelong journey of learning and exploration of new scientific ideas—and will bring thoughtful perspectives, empathy, creativity, and a positive attitude to solve problems s role is ideal for someone looking to extend their Data Science, machine learning and software engineering skills to lead an AI/ML engineering team and create impact by delivering AI/ML capabilities at scale.

Responsibilities:

• Architect, build, maintain scalable systems using established design patterns, leads security-first practices, and maintains deep domain expertise while anticipating future technical needs and costs

• Implement end-to-end solutions for batch and real-time algorithms along with tooling around monitoring, logging, automated testing, performance testing and A/B testing

• Collaborate with Product, Engineering, Data Scientists, ML Engineers and Business teams on planning new capabilities

• Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation

• Write efficient and well-organized software to ship products in an iterative, continual-release environment

• Reviews and prioritizes epics/projects with proper breakdown and dependency management, proactively identifies and communicates blockers or delays, handles uncertainty and high-pressure situations decisively, and applies economic thinking to optimize value delivery

• Mentor teammates to adopt best practices in writing and maintaining production machine learning code and growth opportunities, fosters cultures of effective communication, feedback, and knowledge sharing, builds strong cross-functional relationships, and collaborates on engineering strategy while contributing to product roadmap development.

We're excited about you if you have:

• 5+ years experience developing and deploying machine learning systems into production

• 8+ years experience in Software Engineering

• 2-4 years experience working with AI Agentic systems, LLMs, and RAG architecture

• Experience working with MCP (Model Context Protocol)

• Experience…