Senior MLOps Engineer

Summary

Join our mission to protect cross-border transactions and help customers send money safely worldwide as a Senior MLOps Engineer. You will architect high-performance systems for fraud detection and regulatory compliance, focusing on tabular modeling within our ML stack. Develop and implement a comprehensive MLOps strategy, design and maintain scalable automated pipelines, and build internal tools for versioning, model registry, CI/CD, and observability. Collaborate with cross-functional teams on infrastructure for machine learning workloads and own the full development lifecycle. Work closely with data scientists and other stakeholders to understand model requirements and data dependencies. Enhance fraud detection systems using machine learning. This role requires strong programming skills in Python and experience with various tools and technologies.

Requirements

• 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+)

Responsibilities

• 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

Preferred Qualifications

• Familiarity with Golang, .NET - would be a plus!
• Knowledge of fraud prevention, fintech, or compliance - would be a plus!

Benefits

• 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