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Senior ML Ops Engineer - São Paulo / SP

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Área de AtuaçãoDiversos / Outros

O que você irá fazer

Neither are we.
Because were out to create Better Care for a Better World, and that takes a certain kind of person and teams who care about making a difference.
Here, youll bring your professional expertise, talent, and drive to building and managing our portfolio of iconic, ground-breaking brands.
In your role, youll help us deliver better care for billions of people around the world.
It starts with YOU.
About Us Huggies.
Kleenex.
Cottonelle.
Scott.
Kotex.
Poise.
Depend.
Kimberly-Clark Professional.
You already know our legendary brandsand 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 wouldnt exist without talented professionals, like you.
At Kimberly-Clark, youll be part of the best team committed to driving innovation, growth, and impact.
Were founded on 150 years of market leadership, and were always looking for new and better ways to perform so theres your open door of opportunity.
Its all here for you at Kimberly-Clark; you just need to log on! Led by Purpose.
Driven by You.
About You Youre 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, were constantly exploring new ideas on how, when, and where we can best achieve results.
When you join our team, youll 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.
In your Senior ML Ops Engineer role, youll 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.
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.
Key Responsibilities: As a Senior ML OPS Engineer, youll be part of the NA Advance Analytics team dedicated to productionizing machine learning applications and systems at scale.
Youll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
Youll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
Youll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers that support, build, and enable Machine Learning capabilities across the NA organization.
Youll work closely with internal customers, data & analytics, and cloud team to build our next generation data science workbench and ML platform and products.
Youll 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.
Implement scalable and reliable systems leveraging cloud-based architectures, technologies, and platforms to handle model inference at scale.
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.
Implement security best practices for machine learning systems and ensure compliance with data protection and privacy regulations.
Collaborate with platform engineers to effectively manage cloud compute resources for ML model deployment, monitoring, and performance optimization.
Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes, tools, and best practices.
Technical Skills: Bachelors 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 MLOps, 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.
Experience in building and managing streaming and batch inferencing.
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.
Professional Skills: Strong multi-cultural leadership and management skills.
Strong communication and interpersonal skills.
Strong analytical and problem-solving skills and passion for product development.
Strong understanding of Agile methodologies and open to working in agile environments with multiple stakeholders.
Professional attitude and service orientation; team player.
Ability to translate business needs into potential analytics solutions.
Strong work ethic: ability to work at an abstract level and gain consensus.
Ability to build a sense of trust and rapport to create a comfortable and effective workplace.
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.
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.

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