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Machine Learning Engineer

4 weeks ago
Europe
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Airflow AWS CI/CD Databricks Docker Kafka Kubeflow Kubernetes LLM Machine Learning MLflow MLOps Vertex AI
Apply Now

Yuno

Yuno is a payment orchestration and financial infrastructure platform for global businesses. It centralizes payment methods, PSPs, fraud tools, routing, reconciliation, checkout, payouts, and other payment workflows through a single API.

Payment Processing Software
51-200
Founded 2022
View All Jobs 32

Description

  • Design, build, and maintain the MLOps platform, including experiment tracking, model registries, versioning, and reproducible training pipelines.
  • Establish CI/CD practices for machine learning with automated testing, validation gates, and development-to-production promotion workflows.
  • Productionize models as scalable batch, online, and real-time inference services with low latency and high availability.
  • Implement monitoring for model performance, data drift, and concept drift, including alerting and rollback mechanisms.
  • Automate model retraining, evaluation, deployment, self-healing, and rollback processes.
  • Integrate models with Kafka, Kinesis, Flink, or similar streaming platforms for real-time features and inference.
  • Ensure consistency between offline training features and online serving features.
  • Design agentic workflows using LLM-based agents and tool-calling pipelines, with appropriate observability, guardrails, and evaluation.
  • Collaborate with data science, platform, and product teams to meet production requirements for latency, cost, reliability, and scale.

Requirements

  • 5–8 years of experience in ML engineering, MLOps, or backend infrastructure supporting machine learning systems in production.
  • Strong software engineering fundamentals and experience owning services end to end.
  • Experience with model serving frameworks such as Seldon, KServe, BentoML, or TorchServe.
  • Experience with orchestration tools such as Airflow, Kubeflow, or MLflow.
  • Hands-on experience with streaming systems such as Kafka, Kinesis, or Flink.
  • Familiarity with Docker and Kubernetes.
  • Experience with observability tooling for machine learning or distributed systems, including metrics, tracing, and logging.
  • Strong communication skills and ability to work cross-functionally.
  • Fluent English and residence in Europe.
  • Preferred: experience with LLM and agent frameworks, regulated or high-throughput industries, cloud ML platforms, or open-source MLOps and agentic tooling.

Benefits

  • Competitive compensation.
  • Remote work from anywhere.
  • One-time home office setup allowance and company-provided equipment.
  • Stock options.
  • Health plan available wherever you are.
  • Flexible days off.
  • Language, professional, and personal development courses.

Interested in this position?

Apply directly on the company website

Apply Now

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