Machine Learning Operations Expert

5 days ago


Remote, Czech Republic Devire Full time
Job Description:
Devire IT Outsourcing is a unique cooperation dedicated to IT professionals, based on the principles of own business - B2B, implementing projects for clients running innovative and modern projects.

The client is one of the world's largest food and beverage companies. They are seeking a skilled MLOps professional who will join their Data Science Hub Europe and collaborate with data scientists, data analysts, and engineers to build, scale, and operate their machine learning & analytics platform. The right candidate will contribute to critical business decisions in areas of supply chain and marketing by leveraging their expertise in ML Ops.

Key Responsibilities:
  • Participate in the end-to-end lifecycle of data science projects through DevOps, code, experiment, and model management
  • Design and lead monitoring, troubleshooting, debugging, and incident management for ML pipelines
  • Develop well-designed, testable, efficient code and work closely with engineering to improve data consumption and model deployment in production
  • Collaborate with stakeholders to provide guidance on scaling, throughput, infrastructure, and deployment strategies for ML Ops

Required Skills and Qualifications:
Azure Cloud and Databricks Experience:
Proficiency in Azure cloud environment and Databricks, including setup and maintenance as an ML platform.

Programming Skills:
Advanced proficiency in Python and SQL in version control systems (git) plus their use in building ML & data pipelines.

Software Development Best Practices:
Proven experience with software development best practices including testing, continuous integration, and DevOps tools.

Data Science Knowledge:
Good understanding of data science lifecycle and the way data scientists work to deliver value.

Agile Software Development Lifecycle:
Familiarity with agile software development lifecycle (SCRUM, Kanban, etc.).

Communication Skills:
Business-ready command of English, written and spoken.

Nice to Have:
  • Experience in release on production ML tools involving a user interface, e.g. Dash, Shiny R, Streamlit
  • Experience in Azure cloud resource set up for purposes of data solutions
  • Great communication skills to guide audiences of broad technical knowledge range through complex ML Ops topics
  • Practice coaching/mentoring younger team members in your expertise areas


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