Secure Global Money Transfers with Cutting-Edge Technology.
Join our mission to protect cross-border transactions, helping customers send money safely worldwide.
As a Senior DevOps / ML Infrastructure Engineer in our AI Lab, you'll maintain and scale our infrastructure while enabling seamless ML model integration into production workflows.
You'll work alongside our Senior MLOps Architect to build a comprehensive ML platform that serves multiple teams across the organization.
What You'll Do:
Manage multiple orchestration platforms: Kubernetes in AWS (CloudFormation) and on-prem Kubernetes clusters-Maintain Apache Flink infrastructure (managed in AWS or self-hosted in on-prem Kubernetes)Handle production support, incident response, and on-call rotationsPerform regular patching activities and security vulnerability remediationSupport and maintain workflow engine infrastructureImprove observability by utilizing Prometheus, Grafana, Splunk, Slack alerts, etc.
MLOps & Platform Development:
Collaborate with Senior MLOps Architect to build and maintain ML infrastructureSet up and configure MLflow for experiment tracking and model registryBuild automated MLOps pipelines for model training, experimentation, and deployment (Champion-Challenger, shadow mode)Support feature calculation pipelines and ETL processesEnable model serving infrastructure for Python-based ML services
We're Looking For:
3-5+ years of professional experience in DevOps or infrastructure engineeringStrong hands-on experience with AWS services (EKS, ECR, SQS, S3, Managed Kafka, Managed Prometheus)Deep experience with Kubernetes in production environments (multi-cluster management is a plus)Proficiency with infrastructure as code: AWS CloudFormation and CDK (AWS Cloud Development Kit)Experience with containerization (Docker) and container orchestrationKnowledge of setting up and maintaining CI/CD pipelines (GitHub Actions, ArgoCD, Jenkins, etc.)Hands-on experience with observability tools: Prometheus, Grafana, Splunk- Experience with production support, incident response, and on-call rotationsStrong communication skills (English B2+)Ability to work collaboratively with cross-functional teams (MLOps engineers, data scientists, software engineers)
It would be a plus:
Experience with Apache Flink, Kafka, or other stream processing frameworksUnderstanding of ML lifecycle: model training, evaluation, deployment patternsExperience with workflow engines or rule enginesKnowledge of fraud prevention, fintech, or compliance domainsUnderstanding of feature stores, ETL pipelines, and data engineering concepts
What We Offer:
Remote work flexibility – work from anywhere- B2B contract with competitive gross compensation in USDTop-tier hardware to support your productivityA challenging role in a team of skilled professionals with opportunity to grow into MLOps specializationDirect collaboration with Senior MLOps Architect to learn and contribute to ML platform developmentContinuous learning and career growth opportunitiesCoverage for professional development: training, seminars, and conferencesAccess to high-quality English lessonsImpact: Your work will directly prevent fraud while enabling secure financial access globally
