Senior ML Ops Engineer

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 yourML Ops Engineer Senior 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

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.

Main Responsibilities:

• You ’ll be part of the NA Data Science lean software team dedicated to productionizing machine learning applications and systems at scale.

• You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.

• You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.

• You’ll work closely with internal customers, data & analytics, and cloud team to build our next generation data science workbench and ML platform and products.

• You’ll be able to further expand your knowledge and develop your expertise in modern Machine Learning frameworks, libraries and technologies while working closely with internal stakeholders to understand the evolving business needs.

• Deploy and manage machine learning & data pipelines in production environments.

• Work on containerization and orchestration solutions for model deployment.

• Participate in fast iteration cycles, adapting to evolving project requirements.

• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.

• Leverage CICD best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.

• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

• Collaborate with Data scientists, software engineers, data engineers, and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, monitoring, alerting and automated model deployment.

• Manage and monitor machine learning infrastructure, ensuring high availability and performance.

• Implement robust monitoring and logging solutions for tracking model performance and system health.

• Monitor real-time performance of deployed models, analyze performance data, and proactively identify and address performance issues to ensure optimal model performance.

• Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability in a timely and efficient manner.

• Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes, tools, and best practices.

Key Qualifications and Experiences:

• 
  Bachelor’s degree in management information systems/technology, Computer Science, Engineering, or related discipline. MBA or equivalent is preferred.

• 10+ years of experience as part of large, remote, global IT teams. 7+ years focused on development lifecycle product architecture design.

• 5+ years proven experience in an engineering role with a focus on ML Ops, Data Engineering, ML Engineering.

• 5+ years of experience in ML Lifecycle using Azure Kubernetes service, Azure Container Instance service, Azure Data Factory, Azure Monitor, Azure DataBricks building datasets, ML pipelines, experiments, logging, and monitoring. (Including Drifting, Model Adaptation and Data Collection).

• 5+ years of experience in an execution role engaging with Data Scientists to deliver large scale analytics solutions and projects.

• 5+ years of experience in data engineering using Snowflake.

• Knowledge of machine learning model training, building, algorithm selection and interpretability.

• Experience in designing, developing & scaling complex data & feature pipelines feeding ML models and evaluating their performance

• Proficiency in SQL and any one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA – knowledge of optimization engines such as CPLEX or Gurobi is a plus)

• Strong experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes)

• Experience with CI/CD tools such as GitHub Actions, GitLab, Jenkins, or similar tools.

• Experience with ML frameworks and libraries (TensorFlow, PyTorch, Scikit-learn).

• Familiarity with security best practices in DevOps and ML Ops.

• Experience in developing and maintaining APIs (e.g.: REST)

• Agile/Scrum operating experience using Azure DevOps.

• Experience with MS Cloud - ML Azure Databricks, Data Factory, Synapse, among others.

Total Benefits

Here are just a few of the benefits you’d enjoy working in this role for Kimberly-Clark. For a complete overview, see

Great support for good health with medical, dental, and vision coverage options with no waiting periods or pre-existing condition restrictions. Access to an on-site fitness center, occupational health nurse, and allowances for high-quality safety equipment.

Flexible Savings and spending accounts to maximize health care options and stretch dollars when caring for yourself or dependents.

Diverse income protection insurance options to protect yourself and your family in case of illness, injury, or other unexpected events.

Additional programs and support to continue your education, adopt a child, relocate, or even find temporary childcare.

To Be Considered

Click the Apply button and complete the online application process. A member of our recruiting team will review your application and follow up if you seem like a great fit for this role.

In the meantime, check out the career’s website. You’ll want to review this and come prepared with relevant questions when you pass GO and begin interviews.

For Kimberly-Clark to grow and prosper, we must be an inclusive organization that applies the diverse experiences and passions of its team members to brands that make life better for people all around the world. We actively seek to build a workforce that reflects the experiences of our consumers. When you bring your original thinking to Kimberly-Clark, you fuel the continued success of our enterprise. We are a committed equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation, gender, identity, age, pregnancy, genetic information, citizenship status, or any other characteristic protected by law. The statements above are intended to describe the general nature and level of work performed by employees assigned to this classification. Statements are not intended to be construed as an exhaustive list of all duties, responsibilities and skills required for this position.

Additional information about the compensation and benefits for this role are available upon request. You may contact for assistance. You must include the six digit Job # with your request.

This role is available for local candidates already authorized to work in the role’s country only. Kimberly-Clark will not provide relocation support for this role.

Additional information about the compensation and benefits for this role are available upon request. You may contact for assistance. You must include the six digit Job # with your request.

This role is available for local candidates already authorized to work in the role’s country only. Kimberly-Clark will not provide relocation support for this role.