Senior ML Ops Engineer

You re driven to perform at the highest level possible, and you appreciate a performance culture fueled by authentic caring. You want to be part of a company actively dedicated to sustainability, inclusion, wellbeing, and career development.

You love what you do, especially when the work you do makes a difference. At Kimberly-Clark, we re constantly exploring new ideas on how, when, and where we can best achieve results. When you join our team, you ll experience Flex That Works: flexible work arrangements that empower you to have purposeful time in the office and partner with your leader to make flexibility work for both you and the business.

You were made to do this work: designing new technologies, diving into data, optimizing digital experiences, and constantly developing better, faster ways to get results. You want to be part of a performance culture dedicated to building technology for a purpose that matters. You want to work in an environment that promotes sustainability, inclusion, wellbeing, and career development. In your Senior ML Ops Engineer role, you ll help us deliver better care for billions of people around the world.

Kimberly-Clark is on a mission to transform to become a data driven and AI-First company. Our enterprise vision is to embed an algorithm into every K-C decision, process, and product. To support this vision, Kimberly-Clark North America (KCNA) is investing in the growth of our high-performance Advanced Analytics Team, and we are looking for entrepreneurial-minded innovators to join us in our journey.

The purpose of this agile central team is to develop high-risk, high-reward data science solutions that will unlock future growth of analytics-based solutions across the enterprise.

This newly created individual contributor role will report to the Advance Analytics Engineer Manager and will build our muscle around machine learning capabilities.

As ML Ops Engineer, you will work with Data Scientists, Data Architects and Data Engineers to translate prototypes into scalable solutions. You will build, deploy, run, and monitor ML & AI solutions bridging the gap between Data Scientists and Operations. You will ensure that models conform to the ML strategy and guidance established. You should be proficient at building, training, deploying, and monitoring ML models.

 

Scope/Categories:

Role will report to the ML Ops Engineer Manager.

Travel may include approximately 15% of work time.

 

Key Interfaces

Internal: Data Science Team, Data & Analytics Team, Data & Analytics Product Managers and Product Teams, D&A COE, Cloud COE, UX Designers, Web Apps Developers, Enterprise Architecture, Cyber Security Team, Legal Team.

External: Contractors, Consulting Partners, 3rd Party service providers.

 

Key Responsibilities:

Extended Responsibilities :

Technical Skills:

Professional Skills: