Lead Engineer, AI and Machine Learning

Sephora

Full-time - Mid Level

Hybrid

10,001+ employees

Health and Personal Care Retailers

About the position

As a Lead Machine Learning Engineer at Sephora, you will drive machine learning initiatives across the enterprise, operationalizing innovative ML solutions and collaborating with cross-functional teams. This role focuses on architecting, designing, and building ML pipelines, integrating ML solutions into operational products, and mentoring team members in best practices. You will play a crucial role in redefining customer experiences through AI and machine learning technologies.

Responsibilities

• Lead and execute ML operationalization across the 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 for monitoring, logging, automated testing, performance testing, and A/B testing.
• Identify new opportunities to optimize business processes and improve consumer experiences, prototyping solutions to demonstrate value.
• 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.
• Participate in code reviews and test solutions to ensure they meet best practice specifications.
• Promote good software engineering practices across the team.
• Mentor and educate team members on best practices in writing and maintaining production machine learning code.
• Communicate complex technical concepts to both technical and non-technical audiences.

Requirements

• 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 the software engineering space.
• Experience with relational SQL and NoSQL databases.
• Experience with Hadoop, Spark, Kafka, Scala, Python, R, etc.
• Knowledge of cloud platforms such as Azure or AWS.
• Experience designing, deploying, and administering scalable systems on Microsoft Azure.
• Hands-on experience with Databricks and deep learning frameworks like PyTorch, TensorFlow, Keras.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Experience building and operationalizing feature stores and distributed systems.

Nice-to-haves

• Experience with deploying real-time ML systems on Azure Cloud through frameworks such as ONNX, MLEAP, TF Serving.
• Familiarity with open-source LLMs and LLMOPs.
• Knowledge of data pipeline and workflow management tools.
• Relevant working experience with Kubernetes.

Benefits

• Comprehensive health, dental, and vision plans.
• 401(k) plan with company match.
• Various paid time off programs.
• Employee discount and perks.
• Life insurance and disability insurance.
• Flexible spending accounts.
• Employee referral bonus program.