Lead Engineer, AI and Machine Learning

$181,440 - $201,600/Yr

Sephora - San Francisco, CA

Full-time - Mid Level

Hybrid - San Francisco, CA

5,001-10,000 employees

Health and Personal Care Retailers

About the position

The Lead Engineer, AI and Machine Learning at Sephora is responsible for driving machine learning initiatives across the enterprise. This role involves operationalizing innovative ML solutions, collaborating with various teams, and integrating ML solutions into operational products. The position requires a strong background in ML engineering and MLOps, with a focus on delivering impactful ML capabilities at scale.

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 building and operationalizing feature stores and real-time ML systems on Azure Cloud.

Nice-to-haves

• Experience with distributed systems and service-oriented architectures.
• Familiarity with deploying real-time ML systems using frameworks like ONNX, MLEAP, TF Serving.
• 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.