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 rotations
Perform regular patching activities and security vulnerability remediation
Support and maintain workflow engine infrastructure
Improve observability by utilizing Prometheus, Grafana, Splunk, Slack alerts, etc.
MLOps \& Platform Development:
Collaborate with Senior MLOps Architect to build and maintain ML infrastructure
Set up and configure MLflow for experiment tracking and model registry
Build automated MLOps pipelines for model training, experimentation, and deployment (Champion-Challenger, shadow mode)
Support feature calculation pipelines and ETL processes
Enable model serving infrastructure for Python-based ML services
We're Looking For:
3-5+ years of professional experience in DevOps or infrastructure engineering
Strong 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 orchestration
Knowledge 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 rotations
Strong 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 frameworks
Understanding of ML lifecycle: model training, evaluation, deployment patterns
Experience with workflow engines or rule engines
Knowledge of fraud prevention, fintech, or compliance domains
Understanding 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 USD
Top-tier hardware to support your productivity
A challenging role in a team of skilled professionals with opportunity to grow into MLOps specialization
Direct collaboration with Senior MLOps Architect to learn and contribute to ML platform development
Continuous learning and career growth opportunities
Coverage for professional development: training, seminars, and conferences
Access to high-quality English lessons
Impact: Your work will directly prevent fraud while enabling secure financial access globally
Why This Role:
This position offers a unique opportunity to work at the intersection of traditional DevOps and MLOps. You'll maintain critical infrastructure while building expertise in ML infrastructure, model deployment, and workflow integration. You'll complement our MLOps Architect by handling general infrastructure needs while growing your ML platform skills, ultimately enabling faster delivery of ML capabilities across the organization.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.