Live the experience. From professional empowerment to continual learning opportunities. From ongoing investment in new and emerging technologies to a career of self-determination. At Ulta Beauty, our tech team is critical to our scalability—and is recognized that way. We’ve been defined as a “mature start-up.” A place where interdepartmental exposure, open doors, and genuine collaboration is ubiquitous. Where challenges come fast and furious, requiring agility, mental dexterity, and creativity. Where our passion for better solutions drives us and is core to who we are.

We’re engineering for the future of retail, and it’s no-holds-barred. But for those motivated by continual change and ambiguity, by superior leadership, by whip smart colleagues who will press you daily for your very best, you’ll find that virtually nothing’s impossible at Ulta Beauty.

THE IMPACT YOU CAN HAVE: 

The Senior ML Ops Engineer is responsible for supporting, planning and coordinating functional and technical activities related to machine learning in a highly dynamic and fast paced environment. They work alongside with data engineers, analysts and data scientists to deliver scalable robust innovative AI solutions. This position plays a key role in ensuring successful operations of real-time data pipelines and machine learning solutions on our big data platform to enhance Ulta guest experience.

As an MLOps Engineer, primary responsibility is to build, maintain and constantly improve ML powered solutions to drive better outcomes for Ulta users. You will be managing machine learning lifecycle and operations using Google Cloud Platform, Databricks and Docker to scale our data and model inference pipelines so we can build robust ML services.

YOU'LL ACCOMPLISH THESE GOALS BY:

• Develop frameworks and applications for large-scale data processing evaluating emerging technologies and approaches that will power data-driven capabilities across the Enterprise.
• Develop ML engineering solutions on Google Cloud Platform leveraging Databricks platform to process data, define workflows and schedule jobs.
• Develops a ML Ops end to end process which will enable model development, training, deployment, monitoring and inference.
• Supports the operations of the deployed solutions, investigates complex issues and assists with the resolution and implementation of preventive measures.

• Implement dashboards to monitor the performance of the pipelines and models.
• Work with data scientists, ML and data engineers, to develop robust, highly scalable AI/ML infrastructure and deployment services for our machine learning applications.
• Leverage skills in modern data architecture, cloud engineering, data transformation, and management of structured and unstructured data sources.
• Establish and set up model life cycle management
• Develop and implement strategies for optimizing the performance and scalability of machine learning models in production.
• Implement and maintain data pipelines for AI/ML models.
• Monitor and optimize the performance of AI/ML models in production.
• Stay up to date with the latest AI/ML technologies and best practices and help promote their adoption within the organization.
• Develop and maintain automation tools and processes for deploying and scaling machine learning models.
• Ensure the security and compliance of the machine learning infrastructure, including data privacy and protection regulations.

ESSENTIALS FOR SUCESS: 

• Bachelor’s degree in Computer Science, a related field, or applicable work experience.
• 5 years of overall IT and 3 years of ML Ops experience in Databricks on AWS, Azure or GCP cloud (GCP preferred).
• In-depth understanding of Big Data ecosystems underlying architectures to re-platform legacy systems and build integration solutions on Google Cloud platform.
• Experience Have a passion for new technologies, continuous improvement and actively involved with the team to design new data solutions, monitoring and alerting policies for data solutions.
• Expertise in Java, Python or any scripting language, SQL/NoSQL Database systems.
• Experience in Big Data tools and technologies such as Big Query, Databricks, Airflow, Spark, Kafka Streams
• Experience in test automations ensuring data quality, continuous integrations build and deployment processes using Docker, GitHub, Jenkins and Unix/Linux shell scripts.
• Experience with CI/ CD tools to deploying ML services and applications to at least one major cloud platform (AWS, Azure, GCP)
• Experience building and deploying microservices as part of Machine Learning/Data Science applications.
• Experience in a data science or engineering role applying ML to solve business problems.

• Experience with best-in-class ML operations to monitor and maintain models in production and ensure top quality, stable predictions with high uptime.
• Proven track record of developing and deploying models on Databricks platform on GCP or other cloud services like Amazon SageMaker or Azure ML.
• Hands-on experience in operationalizing AI/ML models, particularly in the retail domain.

• Experience with building continuous integration and delivery pipelines for Machine Learning applications.

• Strong understanding of machine learning algorithms, model evaluation, and optimization techniques.

• Possess a strong work ethic; takes pride in producing a quality product and a strong team player.
• Work with production support and project consultants in an onshore / offshore model.
• Support off-hours production issues and code deployments as needed.
• Minimal travel required.

At Ulta Beauty (NASDAQ: ULTA), the possibilities are beautiful. Ulta Beauty is the largest North American beauty retailer and the premier beauty destination for cosmetics, fragrance, skin care products, hair care products and salon services. We bring possibilities to life through the power of beauty each and every day in our stores and online with more than 25,000 products from approximately 500 well-established and emerging beauty brands across all categories and price points, including Ulta Beauty’s own private label. Ulta Beauty also offers a full-service salon in every store featuring—hair, skin, brow, and make-up services.

We will consider for employment all qualified applicants, including those with arrest records, conviction records, or other criminal histories, in a manner consistent with the requirements of any applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act.