Lead Machine Learning Engineer (San Francisco) Job at LVMH, San Francisco, CA

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  • LVMH
  • San Francisco, CA

Job Description

Lead Machine Learning Engineer

Location: San Francisco, United States

Job Type: Permanent Job

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: Our technology team works fast and smart. We bring new tech to market seriously, developing the latest in mobile technologies, scalable architecture, and the coolest in-store client experience.

Your role at Sephora: This is an opportunity for a Lead Machine Learning Engineer to drive AI / ML initiatives for the enterprise. Sephora continues to inspire our loyal customers in the 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

Responsibilities

  • Architect, build, maintain scalable systems using established design patterns, lead security-first practices, and maintain 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 wellorganized software to ship products in an iterative, continualrelease environment
  • Review and prioritize epics/projects with proper breakdown and dependency management, proactively identify and communicate blockers or delays, handle uncertainty and highpressure situations decisively, and apply economic thinking to optimize value delivery
  • Mentor teammates to adopt best practices in writing and maintaining production machine learning code and growth opportunities, foster cultures of effective communication, feedback, and knowledge sharing, build strong crossfunctional relationships, and collaborate on engineering strategy while contributing to product roadmap development

Qualifications

  • 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 using open source LLMs and LLMOPs
  • 3-5 years experience working with relational SQL and NoSQL databases
  • Experience working with Spark, Kafka, Scala, Python, etc.
  • Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras or similar
  • Experience with objectoriented/objectfunction scripting languages: Python, Java, C++, Scala, etc.
  • Experience building and operationalizing feature stores
  • Experience working with distributed systems, serviceoriented architectures, and designing APIs
  • Excellent communication skills, with the ability to explain complex technical concepts to technical and nontechnical audiences
  • Knowledge of cloud platforms, e.g. Azure, AWS or equivalent
  • Microsoft Azure: Expertise designing, deploying, and administering scalable, available, and faulttolerant systems on Azure
  • Handson experience with Databricks
  • Familiarity in deploying realtime ML systems on Azure Cloud through frameworks such as ONNX, MLEAP, TF Serving, etc.
  • Knowledge of data pipeline and workflow management tools
  • Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation
  • Relevant working experience with Kubernetes

Compensation

Annual base salary range: $186,390.00 - $207,100.00. The actual base salary offered depends on qualifications, experience, unique skills, education, certifications, and geographic location. Individuals may also be eligible to earn bonuses.

Benefits

  • Comprehensive health, dental and vision plans
  • Superior 401(k) plan
  • Various paid time off programs
  • Employee discount/perks
  • Life insurance
  • Disability insurance
  • Flexible spending accounts
  • Employee referral bonus program

While at Sephora, you'll enjoy:

  • The people surrounded by some of the most talented leaders and teams.
  • The learning we invest in training and development, allowing continuous skill growth through personalized career plans.
  • The culture our global reach makes us a leading beauty retailer within the LVMH family, united by a common goal to reimagine the future of beauty.

Sephora is an equal opportunity employer and values diversity. We do not discriminate on the basis of race, religion, color, national origin, ancestry, citizenship, gender, gender identity, sexual orientation, age, marital status, military/veteran status, or disability.

Sephora is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. We consider all qualified applicants with criminal histories in a manner consistent with applicable law.

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Job Tags

Permanent employment, Full time, Work experience placement, Flexible hours,

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