MLOps Engineer

As an MLOps Engineer, you’ll be at the heart of our customer analytics initiatives – designing, building, and maintaining machine learning infrastructure and pipelines that enable our data science and engineering teams to deploy models efficiently and reliably. You’ll collaborate closely with data scientists, pricing analysts, engineers, and business stakeholders to ensure our machine learning architecture is robust, scalable, and future-ready.

You will be responsible for

Model Deployment & Automation

• Develop and manage scalable ML pipelines for training, validation, and deployment.
• Automate model versioning, packaging, and deployment processes using CI/CD tools.
• Implement reproducible model training and serving workflows.
• Assess current solutions, identify risks, and propose improvements.
• Develop infrastructure concepts and actionable roadmaps for short-, medium-, and long-term goals.
• Ensure seamless integration with other data sources and systems across the organization.

Data Engineering & Infrastructure

• Design and maintain Azure Databricks, Datafabric, and Datalake infrastructure for ML workloads.
• Design and reuse datasets for modeling, mining, reporting, and production.
• Explore and integrate new internal and external data sources in a GDPR-compliant manner.
• Optimize compute resource usage for cost-efficiency and performance.

Monitoring & Maintenance

• Build monitoring systems to track model performance, data drift, and operational metrics.
• Implement automated retraining and rollback mechanisms.
• Ensure ML systems meet SLAs, scalability, and reliability targets.

Cross-Functional Collaboration

• Contribute to initiatives around customer data ownership and quality.
• Educate teams on hypothesis testing, statistical validation, and A/B testing frameworks.
• Automate business processes using Python and other tools.
• Promote model governance, security, and compliance throughout the ML lifecycle.

Continuous Learning & Innovation

• Stay up to date with trends in data science, machine learning, and analytics.
• Share knowledge and foster innovation across the organization.

What do we expect from you?

• Proven experience in MLOps, data engineering, or analytics infrastructure.
• Strong knowledge of ML frameworks and MLOps tools  (e.g. MLflow).
• Familiarity with API development, authorization,  monitoring and logging for APIs (any knowledge of FastAPI for api development, open telemetry compatible logging, docker/Kubernetes based deployments, or other similar tools and frameworks)
• Knowledge of data versioning and model tracking tools.
• Experience with cloud platforms (Azure Databricks, Datafabric, Datalake, and BigQuery).
• Proficiency in Python and experience with automation and orchestration tools.
• Familiarity with monitoring and logging.
• Understanding of digital marketing data flows and BPM systems.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Passion for data quality, governance, and continuous improvement.
• Fluency in English language with the ability to understand one of the Baltic languages.

Our promise to you

For stability

• Monthly salary from €4300 to €5500 gross, depending on candidate’s qualifications and experience. Additionally, there is an annual bonus.
• We offer various financial benefits, including discounts on our products for both you and your family, special gifts for birthdays, among other perks.
• Our primary workplace is the office, but there is a possibility of hybrid work.
• Job location is in Vilnius.

For development

• Stimulating and exciting projects with the freedom to independently plan your tasks.
• Access to personal development and training opportunities.
• Experience a strong international company culture, including company events, captivating speakers, and other inspiring initiatives.

For wellbeing

• Prioritize your wellbeing with health insurance, additional vacation days, different activities in the office, and more.

Read more about our benefits for employees.

Join us!

In case you have any questions, you can contact your possible future leader – Head of Data Unit Ramunė Šabanienė.

By submitting your application you accept our privacy notice.