MLOps Senior [Risk Team]

We are looking for Senior MLOps Engineer to join our Risk team. Risk team is responsible for automated IT solutions in risk management processes. Within this process we solve the tasks for creating models and inference it on production in real-time with specified SLA, integrate tons of external services and make decisions only on data.

Our Data Science team develops scoring models including neural network-based approaches, and we need to industrialize the entire ML lifecycle. We are looking for an MLOps Engineer to build ML infrastructure from scratch — from automated training pipelines to a unified feature platform serving both DWH research and real-time production inference.

Challenges That Await You

Conduct evaluation of Feature Store / Feature Registry solutions (Feast, Tecton, or custom), prepare a recommendation, design the architecture and feature lifecycle process (experiment → stable → production). Lead the implementation by engineering and platform teams

Design, build, and own ML training and deployment pipelines: experiment tracking, model registry, CI/CD for models, packaging and handoff to production. Select the platform (MLflow or alternatives), establish versioning and validation standards, and evolve the infrastructure continuously

Select tooling and set up monitoring of model quality (drift, degradation) and feature health (freshness, data quality) in collaboration with the DS team. Define the alerting and response process

What Makes You a Great Fit

3+ years of experience in ML Engineering, Data Engineering, or DevOps with hands-on involvement in deploying and maintaining ML systems in production

Experience building ML training pipelines with experiment tracking and model registry (MLflow, W&B, or similar)

Understanding of feature store concepts and train-serve consistency challenges

Strong Python skills; understanding of ML frameworks enough to package, serve, and debug models

Experience with Docker and ML pipeline orchestration (Kubeflow, Argo Workflows, Metaflow, or similar)

Solid SQL skills and understanding of data warehouse architecture

B1 or higher English level for effective communication with an international team

Our ways of working:

Innovative Spirit: A commitment to creativity and groundbreaking solutions

Honest Feedback: valuing open, transparent communication

Supportive Team: a strong, collaborative community

Celebrating Achievements: recognizing our wins together

High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances

Our benefits:

Relocation support to one of our hubs — Cyprus, Serbia, Georgia or Kazakhstan — with assistance for the employee and their family

Flexible work from one of our offices or remote

Healthcare Coverage

Education Budget: Language lessons, professional training and certifications

Wellness Budget: Mental health and fitness activity reimbursements

Vacation policy: 20 days of annual leave and paid sick leave