As a key member of the Data Science Hub Europe you will be part of a team dedicated to delivering efficient and high-quality data solutions. You will collaborate with data scientists, data analysts and engineers to build, scale and operate our machine learning & analytics platform. Your skill, competence and creativity will directly support and impact critical business decisions in areas of supply chain and marketing.

ML Ops with Azure / Databricks

Your responsibilities

• Optimize, standardize and implement data science and machine learning solutions at scale and in cloud-based environments (Azure)
• Participate in the end-to-end lifecycle of data science projects through the use of DevOps, code, experiment and model management, CI/CD and further industry best practices
• Write well-designed, testable, efficient code
• Work closely with engineering to continuously improve the way we consume data and deploy models in production
• Design and lead on monitoring, troubleshooting, debugging and incident management for our ML pipelines
• Be a trusted advisor and evangelist to the team and stakeholders on various aspects of ML Ops, from scaling and throughput, to infrastructure and deployment strategies

Our requirements

• 2+ years of professional experience in ML Ops or ML engineering, particularly in productionizing and scaling ML models
• Broad familiarity with Azure cloud environment and Databricks, including its setup and maintenance as an ML platform
• Advanced proficiency with Python and SQL in version control systems (git) plus their use in building ML & data pipelines
• Proven experience with software development best practices including testing, continuous integration, and DevOps tools
• Good understanding of data science lifecycle and the way data scientists work to deliver value
• Familiarity with agile software development lifecycle (SCRUM, Kanban, etc.)
• Attention to clarity of code, ease of development, and correctness of implementations
• Business-ready command of English, written and spoken
• Experience in productionizing ML tools involving a user interface, e.g. Dash, Shiny R, Streamlit
• Experience in Azure cloud resource setup for purposes of data solutions
• Great communication skills to guide audiences of a broad technical knowledge range through complex ML Ops topics
• Practice in coaching / mentoring younger team members in your expertise areas

What we offer

• Exciting work in a multi-cultural team of bright minds – data lovers and practitioners
• Flexible remote work options, or – if your prefer – access to a modern office in Warsaw’s Mokotów, walking distance from Metro Wilanowska
• Internal training programs and access to external knowledge resources aimed at expanding your skills and competence
• Support in building your ML / data ops skills and portfolio through participation and presenting at conferences and events
• Opportunities to develop further in our Data Science Hub as well as in the international organization