Lead Machine Learning Engineer

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 well‑organized software to ship products in an iterative, continual‑release environment

Review and prioritize epics / projects with proper breakdown and dependency management, proactively identify and communicate blockers or delays, handle uncertainty and high‑pressure 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 cross‑functional 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 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

Excellent communication skills, with the ability to explain complex technical concepts to technical and non‑technical audiences

Knowledge of cloud platforms, e.g. Azure, AWS or equivalent

Microsoft Azure : Expertise designing, deploying, and administering scalable, available, and fault‑tolerant systems on Azure

Hands‑on experience 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

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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