ML Engineer, MLOps & Real-Time Inference - Remote

Yuno; España; Remote; PHP 5,810,000 - 8,715,000; Full time

Benefits offered by this job

Remote work from anywhere

Stock options

Health plan

Home office bonus

Work equipment

Flexible days off

Growth courses

Job summary

Yuno is building a global payment infrastructure that enables every company to participate in the market. You will join a team of engineers delivering reliable ML systems and scalable tooling in production, collaborating with data science, platform and product teams to ship impact at scale.

As a mid-level Machine Learning Engineer based in Europe, you will own MLOps, automate model lifecycles, and design streaming pipelines for real-time feature computation.

Qualifications

• 5–8 years of hands-on ML engineering experience in production systems.
• Strong software engineering fundamentals and ownership of services end-to-end.
• Experience with ML serving frameworks and orchestration tools.
• Familiar with streaming platforms (Kafka/Kinesis/Flink) and containerization.
• Fluent English; based in Europe.

Responsibilities

• Design, build and maintain the MLOps platform with experiment tracking and model registry.
• Productionize models: low-latency, scalable serving and monitoring.
• Automate retraining, evaluation and deployment pipelines.
• Integrate ML models with streaming data platforms for real-time feature computation.
• Design agentic workflows with LLM-based agents and guardrails.

Skills

ML engineering

Backend services

Streaming systems

Observability

DevOps

English fluency

Tools

Seldon

KServe

TorchServe

Airflow

Kubeflow

MLflow

Docker

Kubernetes

Kafka

Flink

Job description

Yuno is building a global payment infrastructure that enables every company to participate in the market. You will join a team of engineers delivering reliable ML systems and scalable tooling in production, collaborating with data science, platform and product teams to ship impact at scale.

As a mid-level Machine Learning Engineer based in Europe, you will own MLOps, automate model lifecycles, and design streaming pipelines for real-time feature computation.