Senior ML Ops Engineer 

Senior ML Ops Engineer 

Job Description

Your Job

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.  

About Us

Huggies®.

Kleenex®.

Cottonelle®.

Scott®.

Kotex®.

Poise®.

Depend®.

Kimberly-Clark Professional®.

You already know our legendary brands—and so does the rest of the world.

In fact, millions of people use Kimberly-Clark products every day.

We know these amazing Kimberly-Clark products wouldn’t exist without talented professionals, like you.

At Kimberly-Clark, you’ll be part of the best team committed to driving innovation, growth and impact.

We’re founded on 150 years of market leadership, and we’re always looking for new and better ways to perform – so there’s your open door of opportunity.

It’s all here for you at Kimberly-Clark; you just need to log on!

Led by Purpose.

Driven by You.

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 Data Science and Advanced Analytics Strategy 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 ML Ops Engineer Manager and will build our muscle around machine learning capabilities.  

 

As ML Ops Engineer, you will work with Data Scientists and Data Architects 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.  

 

Main Responsibilities:  


* As a Senior ...