SEPHORA
Lead Machine Learning Engineer
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SEPHORA Job ID: 278398 Location: CA-FSC SF Off (0174) – 350 Mission St, 20th Floor, San Francisco, CA 94105, United States (US) Job Type: Regular | Position Type: Regular | Remote Eligible: Hybrid Schedule Company: SEPHORA 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. Technology Team
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. Opportunity
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 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, foster cultures of effective communication, feedback, and knowledge sharing, build strong cross-functional relationships, and collaborate 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 using open source LLMs and LLMOPs 3-5 years experience working with a variety of 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 object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. Experience building and operationalizing feature stores Experience working with distributed systems, service-oriented architectures, and designing APIs Write efficient and well-organized software to ship products in an iterative, continual-release environment Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences Knowledge of cloud platforms, for example: Experience with Azure, AWS or equivalent cloud platforms
Experience designing, deploying, and administering scalable, available, and fault tolerant systems on Microsoft Azure
Hands-on Experience working with Databricks Familiarity in deploying real-time 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. Salary
The annual base salary range for this position is $186,390.00 - $207,100.00. The actual base salary offered depends on a variety of factors... (the monetary range is kept). 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 Why Work at Sephora
The people: surrounded by some of the most talented leaders and teams. The learning: we invest in training and developing our teams. The culture: as a leading beauty retailer within the LVMH family, our impact is global. EEO Statement
Sephora is an equal opportunity employer and values diversity at our company. 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 status. Sephora is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Sephora will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law.
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at
SEPHORA Job ID: 278398 Location: CA-FSC SF Off (0174) – 350 Mission St, 20th Floor, San Francisco, CA 94105, United States (US) Job Type: Regular | Position Type: Regular | Remote Eligible: Hybrid Schedule Company: SEPHORA 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. Technology Team
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. Opportunity
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 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, foster cultures of effective communication, feedback, and knowledge sharing, build strong cross-functional relationships, and collaborate 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 using open source LLMs and LLMOPs 3-5 years experience working with a variety of 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 object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. Experience building and operationalizing feature stores Experience working with distributed systems, service-oriented architectures, and designing APIs Write efficient and well-organized software to ship products in an iterative, continual-release environment Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences Knowledge of cloud platforms, for example: Experience with Azure, AWS or equivalent cloud platforms
Experience designing, deploying, and administering scalable, available, and fault tolerant systems on Microsoft Azure
Hands-on Experience working with Databricks Familiarity in deploying real-time 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. Salary
The annual base salary range for this position is $186,390.00 - $207,100.00. The actual base salary offered depends on a variety of factors... (the monetary range is kept). 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 Why Work at Sephora
The people: surrounded by some of the most talented leaders and teams. The learning: we invest in training and developing our teams. The culture: as a leading beauty retailer within the LVMH family, our impact is global. EEO Statement
Sephora is an equal opportunity employer and values diversity at our company. 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 status. Sephora is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Sephora will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law.
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