Machine Learning Engineer (MLOps)

Location: Europe; remote

Company

Payment infrastructure connects businesses to more than 300 payment methods worldwide through a single API, using intelligent transaction routing and fraud prevention across more than 80 countries.

What you will do

• Design, build, and maintain the MLOps platform, including experiment tracking, model registries, versioning, reproducible training pipelines, and CI/CD workflows.
• Productionize machine learning models as scalable batch, online, and real-time services with low latency and high availability.
• Implement monitoring for model performance, data drift, and concept drift, including alerting, rollback, and self-healing mechanisms.
• Automate model retraining, evaluation, and deployment so ML practitioners can ship models with less infrastructure expertise.
• Integrate models with Kafka, Kinesis, and Flink for real-time feature computation and inference while maintaining offline-online feature consistency.
• Build reliable agentic ML workflows with observability, guardrails, evaluation frameworks, and tool-calling pipelines.

Requirements

• 5–8 years of experience in ML engineering, MLOps, or backend infrastructure for production ML systems.
• Experience with model serving and orchestration tools such as Seldon, KServe, BentoML, TorchServe, Airflow, Kubeflow, or MLflow.
• Hands-on experience with streaming systems such as Kafka, Kinesis, or Flink.
• Knowledge of Docker, Kubernetes, and observability practices covering metrics, tracing, and logging.
• Strong software engineering, communication, and cross-functional collaboration skills.
• Fluent English and a requirement to be based in Europe.

Nice to have

• Experience with LLM and agent frameworks, evaluation practices, or open-source MLOps and agentic tooling.
• Experience in regulated or high-throughput domains such as fintech, payments, or healthcare.
• Experience with SageMaker, Vertex AI, Databricks, or similar cloud ML platforms.

Culture & Benefits

• Remote work with the stated ability to work from everywhere, subject to the Europe-based role requirement.
• Competitive compensation, stock options, and a health plan.
• One-time home office allowance and work equipment.
• Flexible days off.
• Language, professional, and personal growth courses.