ML Engineer (MLOps) Senior - Risk Team
New
P
Plata CardRisk Management
Cyprus, Serbia, Georgia or KazakhstanFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- B1 or higher English level
- Experience
- 3+ years
- Required Skills
- DockerPythonSQLKubeflowMLFlow
Requirements
- 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
- Experience with ML pipeline orchestration (Kubeflow, Argo Workflows, Metaflow, or similar)
- Solid SQL skills
- Understanding of data warehouse architecture
- B1 or higher English level for effective communication with an international team
Responsibilities
- Conduct evaluation of Feature Store / Feature Registry solutions (Feast, Tecton, or custom)
- Prepare a recommendation for Feature Store / Feature Registry solutions
- Design the architecture and feature lifecycle process (experiment → stable → production)
- Lead the implementation of Feature Store / Feature Registry solutions by engineering and platform teams
- Design, build, and own ML training and deployment pipelines
- Establish experiment tracking and model registry (MLflow or alternatives)
- Implement CI/CD for models, packaging and handoff to production
- Establish versioning and validation standards for ML infrastructure
- Evolve the ML infrastructure continuously
- Select tooling and set up monitoring of model quality (drift, degradation) in collaboration with the DS team
- Set up monitoring of feature health (freshness, data quality) in collaboration with the DS team
- Define the alerting and response process for model and feature health
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