Senior Engineer, Machine Learning

Job ID: 254289
Location Name: FSC REMOTE SF/NY/DC -173(USA_0173)
Address: FSC, Remote, CA 94105, United States (US)
Job Type: Full Time
Position Type: Regular
Job Function: Information Technology
Remote Eligible:Yes

 

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:

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 Senior Machine Learning Engineer to come in and drive the operationalization of AI/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.

As a Senior Machine Learning Engineer, you will work on a broad set of domains that power a data-driven transformation of our standard business procedures across channels. Support the Data Science team in deploying novel algorithms along with optimizing existing machine learning systems to maximize their value and increase consumer satisfaction at every brand touchpoint. 

We are looking for someone who is committed to a lifelong journey of learning and exploration of new technology—and will bring thoughtful perspectives, empathy, creativity, and a positive attitude to solve problems at scale.

 

Responsibilities:
•    Responsible for delivering projects to operationalize AI/ML models across the enterprise, including acting as a center of excellence to drive adoption of ML/AI by autonomous, domain-specific engineering pods.
•    Build, maintain, and improve a suite of new and existing AI/ML systems.
•    Implement end-to-end solutions for both real-time and batch algorithms along with tooling for monitoring, logging, automated testing, performance testing and A/B testing – including integration with existing enterprise systems and customer-facing digital systems.
•    Collaborate with Product, Engineering and Business teams
•    Write efficient, well-organized software to ship products in an iterative, continuous-release environment
•    Good 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:

•    Degree in engineering, computer science, mathematics, or a related field
•    4+ years’ experience in software/application engineering
•    2+ years’ experience developing and deploying machine learning systems into production
•    2+ years’ experience with at least one cloud platform (Azure, GCP, AWS) and associated ML services, including Databricks
•    Strong understanding of fundamental computer science concepts, software design best practices, software development lifecycle and common machine learning design patterns
•    An advocate for modern software engineering methodologies, e.g. Agile, unit testing, test automation, continuous integration, code reviews, design documentation
•    Exceptional in advanced Python programming for AI
•    Expertise working with: Spark, Kafka, and GenAI models and services
•    Solid understanding of foundational machine learning concepts and algorithms, including GenAI
•    Proven experience deploying stable, real-time ML systems 
•    Experience optimizing the model training process for deep learning frameworks such as PyTorch, Tensorflow, Keras or similar
•    Experience working with a variety of relational SQL and NoSQL databases
•    Solid and practical understanding of data pipelines and tools
•    Expertise managing changes in object-oriented applications
•    Experience working with distributed systems, service-oriented architec