Machine Learning and AI Platform Engineer

hace 1 semana

Madrid, Madrid, España Envirorec A tiempo completo

Machine Learning and AI Platform Engineer (LLMs) | Madrid | Fixed term contract until July 2026 | €50k-75k p/a | Hybrid remote WFH | Quantum Computing | Artificial Intelligence

  • Hybrid remote working 2-3 days a week in office, remote WFH the rest of the time
  • Open to EU Citizens only (sponsorship not available)
  • Fixed term temporary contract until 1st July 2026
  • Salary c. €50k-60k p/a for a mid level hire, €65k-75k p/a for a senior
  • Signing bonus, retention bonus and relocation fund available

We're working with a fast-growing deep-tech company building large-scale AI systems used by enterprise clients across multiple industries.

They're looking for a
Machine Learning Platform Engineer / AI Platform Engineer
to help design, deploy and operate production-grade machine learning and AI systems. This is a hands-on engineering role focused on reliability, scalability and automation rather than pure research.

What you'll be working on


• Deploying and operating machine learning and AI models in real production environments


• Building automated pipelines covering training, validation, deployment and monitoring


• Running ML workloads on cloud-native platforms using containers, orchestration and CI/CD


• Improving reliability, performance and observability of ML and AI services


• Collaborating closely with ML engineers, data scientists, backend engineers and infrastructure teams

What we're looking for


• Strong Python engineering background with experience supporting ML systems


• Experience running production services on cloud platforms (AWS, Azure or similar)


• Familiarity with containers, orchestration and automated deployment pipelines


• Understanding of the ML lifecycle and how models behave once deployed


• Comfort working across engineering, infrastructure and data teams

Nice to have (but not essential)


• Experience with ML pipelines, experiment tracking or model serving


• Exposure to large language models, RAG systems or inference optimisation


• Observability, monitoring or platform reliability experience


• Background in data engineering, backend engineering or platform teams

Why this role

This role suits engineers who enjoy:


• owning systems end-to-end


• building platforms others rely on


• working close to production


• solving reliability, scale and performance problems

You don't need to come from a role called "MLOps" though MLOps experience is highly desirable — if you've been enabling ML systems in production, we want to speak with you.

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