MLOps Engineer

About the role

We are looking for an MLOps Engineer to help scale and maintain the infrastructure behind Liz, Seedtag’s contextual AI. The role focuses on reliable, efficient, low‑latency ML model deployment across the open web and Connected TV.

Key responsibilities

• Deploy, maintain and optimise ML models in production, ensuring performance, reliability and latency standards.
• Build and improve data pipelines for dataset generation, model training, validation and performance analysis.
• Implement model observability with monitoring, dashboards, drift detection and alerting.
• Enhance CI/CD pipelines, model versioning, reproducibility and infrastructure automation.
• Identify opportunities to reduce serving costs and improve efficiency.
• Develop internal automations and agentic integrations to streamline ML workflows.
• Collaborate with Data, Platform and Backend teams to troubleshoot production issues.

Required profile

• 2–4 years of experience building, deploying and maintaining ML systems in production.
• Strong Python skills, including APIs, asynchronous programming, testing and clean architecture.
• Hands‑on experience with ML model development and production deployment.
• Solid understanding of MLOps practices such as CI/CD, model versioning and monitoring.
• Experience with ML observability, performance metrics, dashboards and alerting.
• Knowledge of distributed systems, microservices, Kubernetes and cloud infrastructure.
• Strong troubleshooting skills across models, data pipelines, APIs and infrastructure.
• Proactive, curious and autonomous with end‑to‑end ownership.

Required skills

• Python
• Go
• Google Cloud Platform (GCP), Vertex AI
• Kubernetes, Terraform
• MLflow, Weights & Biases, Evidently
• Prometheus, Grafana
• Kafka, Redis, Bigtable, MongoDB
• NLP, embeddings, ranking models, agentic workflows

What we offer

• Flexible work model with 100 % remote or hybrid options.
• Home office setup budget up to €1,000.
• Paid trips to headquarters in Madrid.
• MacBook Pro M3.
• Continuous learning platform and optional language classes.
• Supportive, trust‑based culture with well‑being focus.
• Team activities, offsites and opportunities to connect beyond work.