Lead Engineer, AI and Machine Learning

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 Machine Learning Engineer to come in and drive 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 customer discover products.
• Personalized in-session product recommendation engine (In store and Online)
• Customer Segmentation
• Next-Best offer prediction

As a Lead Machine Learning Engineer, you will operationalize innovative ML solutions and work alongside other team members like product manager, Enterprise architect, Principal ML Engineer, Data scientists and business to architect, design, build ML pipeline and productionalize ML models. You will be also responsible for integrating ML solutions to operational products. This hands-on technical role demands excellent ML engineering and MLops 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 at scale. This role is ideal for someone looking to extend their machine learning and software engineering skills to lead ML engineering team and create impact by delivering ML capabilities at scale.

Responsibilities:

• Responsible for leading and executing ML operationalization across enterprise.
• Architect, build, maintain, and improve end to end ML systems.
• 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
• Utilize your entrepreneurial spirit to identify new opportunities to optimize business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset.
• Collaborate with Product, Engineering , Data scientists 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
• Actively participate in code review and test solutions to ensure it meets best practice specifications.
• Contribute to and promote good software engineering practices across the team
• Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code
• Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences
• Demonstrate our Sephora values of Passion for Client Service, Innovation, Expertise, Balance, Respect for All, Teamwork, and Initiative

We are excited about you if you have:

• University or advanced degree in engineering, computer science, mathematics, or a related field
• 5+ years of experience developing and deploying machine learning systems into production
• 8+ years of experience in Software engineering space.
• Experience working with a variety of relational SQL and NoSQL databases
• Experience working with: Hadoop, Spark, Kafka, Scala, Python, R etc.
• Knowledge of cloud platforms, for example:
• ​ Experience with Azure, AWS or equivalent cloud platforms
• Microsoft Azure: Experience designing, deploying, and administering scalable, available, and fault tolerant systems on Microsoft Azure using HDInsights or Analytics Platform System (APS)
• Experience with Azure Management Portal, Azure Machine Learning, and Azure SQL Server
• Hadoop: Experience with storing, joining, filtering, and analyzing data using Spark, Hive and Map Reduce
• Hands-on Experience working with Databricks.
• 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.
• Industry experiences building and productionizing creative end-to-end Machine Learning systems
• Experience with building and operationalize feature store.
• Experience working with distributed systems, service oriented architectures and designing APIs/ API Graph.
• Familiarity in deploying real-time ML systems on Azure Cloud through frameworks such as ONNX, MLEAP , TF Serving etc.
• Experience using opensource LLMs, LLMOPs.
• 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.