Senior Machine Learning Operations Engineer

2 semanas atrás

São Paulo, São Paulo, Brasil Kimberly-Clark Tempo inteiro
About the Role

We are seeking a highly skilled Senior Machine Learning Operations Engineer to join our Data Science lean software team dedicated to productionizing machine learning applications and systems at scale. As a key member of our team, you will participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.

Key Responsibilities
  • Focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
  • 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.
  • 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.
  • 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.
Requirements
  • 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 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.
  • 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.
About Us

Kimberly-Clark is a leading global consumer goods company with a rich history of innovation and a commitment to making a positive impact on the world. We are dedicated to building a better world for our consumers, customers, and employees.

We are seeking talented individuals who share our passion for innovation, customer satisfaction, and making a difference in the world. If you are a motivated and experienced professional looking for a new challenge, we encourage you to apply for this exciting opportunity.

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