ML Ops Engineer

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.

In this role you will:

• 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

You are the right candidate if you bring along:

• 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

You will draw even more of our attention if you have:

• 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

In return 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
• Opportunity to participate in Sustainability projects and join a community focused on creating sustainable solutions
• A work atmosphere based on respect, professionalism and kindness