Lead Engineer, AI and ML Platform

24 hours ago

San Francisco, California, United States Sephora USA, Inc Full time
About Sephora USA, Inc.

Sephora USA, Inc. is a leading beauty retailer that inspires its customers, empowers its teams, and helps them become the best versions of themselves. We create an environment where people are valued, and differences are celebrated. Our purpose is to expand the way the world sees beauty by empowering the Extra Ordinary in each of us.

The Opportunity

We are seeking a highly skilled Machine Learning Engineer to join our team and help us enable ML platform for the enterprise. As a leader in the beauty industry, we are committed to innovation and excellence, and we are looking for someone who shares our passion for technology and beauty.

Key Responsibilities
  • Lead and Execute ML Operationalization: Responsible for leading and executing ML operationalization across the enterprise, ensuring seamless integration with existing systems and processes.
  • Architect and Build ML Systems: Architect, build, maintain, and improve end-to-end ML systems utilizing ML platform, ensuring scalability, efficiency, and reliability.
  • Implement End-to-End Solutions: 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.
  • Identify New Opportunities: 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 Teams: Collaborate with Product, Engineering, Data scientists, and Business teams on planning new capabilities, ensuring alignment and effective communication.
  • Establish Efficient Processes: Establish scalable, efficient, automated processes for data analyses, model development, validation, and implementation, ensuring data quality and integrity.
  • Write Efficient Software: Write efficient and well-organized software to ship products in an iterative, continual-release environment, ensuring high-quality code and adherence to best practices.
  • Participate in Code Review: Actively participate in code review and test solutions to ensure they meet best practice specifications, promoting a culture of excellence and continuous improvement.
  • Mentor and Educate: Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code, ensuring knowledge sharing and skill development.
  • Excellent Communication: Demonstrate excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences, ensuring effective collaboration and stakeholder management.
Requirements
  • University or Advanced Degree: University or advanced degree in engineering, computer science, mathematics, or a related field.
  • 5+ Years of Experience: 5+ years of experience developing and deploying machine learning systems into production, with a strong track record of success.
  • 8+ Years of Software Engineering Experience: 8+ years of experience in software engineering space, with a focus on machine learning and AI.
  • Experience with Relational SQL and NoSQL Databases: Experience working with a variety of relational SQL and NoSQL databases, ensuring data management and integration.
  • Experience with Cloud Platforms: Experience working with cloud platforms, such as Azure, AWS, or equivalent cloud platforms, ensuring scalability and reliability.
  • Experience with Deep Learning Frameworks: Experience with deep learning frameworks, such as PyTorch, TensorFlow, Keras, or similar, ensuring expertise in machine learning and AI.
  • Experience with Object-Oriented/Object Function Scripting Languages: Experience with object-oriented/object function scripting languages, such as Python, Java, C++, Scala, etc., ensuring proficiency in software development.
  • Industry Experience: Industry experience building and productionizing creative end-to-end machine learning systems, ensuring expertise in AI and ML.
  • Experience with Feature Store: Experience working with feature store, ensuring data management and integration.
  • Experience with Distributed Systems: Experience working with distributed systems, service-oriented architectures, and designing APIs/API Graph, ensuring scalability and reliability.
  • Experience with Real-Time ML Systems: Experience deploying real-time ML systems on Azure Cloud through frameworks such as ONNX, MLEAP, TF Serving, etc., ensuring expertise in AI and ML.
  • Experience with ML Platform: Experience working with ML platform, such as Dataiku, MLFlow, etc., ensuring expertise in AI and ML.
  • Experience with ML Model Monitoring: Experience with ML model monitoring, observability, and governance, ensuring data quality and integrity.
  • Knowledge of Data Pipeline and Workflow Management Tools: Knowledge of data pipeline and workflow management tools, ensuring data management and integration.
  • Expertise in Standard Software Engineering Methodology: Expertise in standard software engineering methodology, such as unit testing, test automation, continuous integration, code reviews, design documentation, ensuring high-quality code and adherence to best practices.
  • Relevant Working Experience with Kubernetes: Relevant working experience with Kubernetes, ensuring scalability and reliability.
About the Role

This is an exciting opportunity to join our team and contribute to the development of innovative machine learning solutions. As a Machine Learning Engineer, you will be responsible for leading and executing ML operationalization across the enterprise, architecting and building ML systems, and implementing end-to-end solutions for batch and real-time algorithms. You will also be responsible for identifying new opportunities to optimize business processes and improve consumer experiences, and collaborating with teams to plan new capabilities.

What We Offer
  • Competitive Salary: A competitive salary and benefits package, including comprehensive health, dental, and vision plans, a superior 401(k) plan, and various paid time off programs.
  • Opportunities for Growth: Opportunities for growth and development, including training and development programs, mentorship, and career advancement opportunities.
  • Collaborative Environment: A collaborative and dynamic work environment, with a team of talented professionals who are passionate about technology and beauty.
  • Recognition and Rewards: Recognition and rewards for outstanding performance, including bonuses and employee recognition programs.

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