Senior MLOps Engineer - Anti-Fraud & Compliance Platform
Join our mission to protect cross-border transactions, helping customers send money safely worldwide.
As a Senior MLOps Engineer in our Anti-Fraud & Compliance team, you'll architect high-performance systems that detect fraud and enforce regulatory compliance. Our ML stack focuses on tabular modeling for fraud detection and prevention.
What You'll Do: * Develop and implement a comprehensive MLOps strategy that enables the seamless integration of machine learning models into our environment. * Design, implement, and maintain scalable and automated MLOps pipelines (data ingestion, training, evaluation, deployment, and monitoring). * Build internal tools or integrate existing solutions for versioning, model registry, CI/CD, and observability. * Collaborate with cross-functional teams to design, deploy, and manage scalable infrastructure for machine learning workloads. * Own the full development lifecycle from design to incident response. * Work closely with data scientists, software engineers, and other stakeholders to understand model requirements, deployment needs, and data dependencies. * Enhance fraud detection systems using machine learning
We offer you:
- Remote work flexibility – work from anywhere.
- B2B contract with competitive gross compensation in USD.
- Top-tier hardware to support your productivity.
- A challenging role in a team of skilled professionals.
- Continuous learning and career growth opportunities.
- Coverage for professional development: training, seminars, and conferences.
- Access to high-quality English lessons.
We're Looking For:
- 5+ years of professional experience in MLOps or a related field.
- Experience deploying and managing machine learning models in production environments.
- Understanding ML lifecycle, model training and evaluation workflows, reproducibility, and model governance.
- Experience building internal MLOps platforms or developer tools.
- Experience with ML pipeline orchestration tools (e.g. Kubeflow, MLflow, Airflow, Metaflow, SageMaker Pipelines).
- Knowledge of setting up CI/CD pipelines for ML workflows using GitHub Actions, GitLab CI, Argo, Jenkins, etc.
- Experience deploying models in Docker/Kubernetes environments.
- Strong knowledge of cloud platforms: AWS, GCP, or Azure.
- Experience with setting up tools like Prometheus, Grafana for model & pipeline observability.
- Strong programming skills in Python.
- Experience with SQL/NoSQL databases and distributed systems.
- Strong communication skills (English B2+)
- *Familiarity with Golang, .NET - would be a plus!
- *Knowledge of fraud prevention, fintech, or compliance - would be a plus!
