Machine Learning and AI Platform Engineer

hace 5 días


Catalonia, España Envirorec A tiempo completo

Machine Learning and AI Platform Engineer (LLMs) | Barcelona | Fixed term contract until July 2026 | €50k-75k p/a | Hybrid remote WFH | Quantum Computing | Artificial IntelligenceHybrid remote working 2-3 days a week in office, remote WFH the rest of the timeOpen to EU Citizens only (sponsorship not available)Fixed term temporary contract until 1st July 2026Salary c. €50k-60k p/a for a mid level hire, €65k-75k p/a for a seniorSigning bonus, retention bonus and relocation fund availableWe'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 teamsWhat 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 teamsNice 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 teamsWhy this roleThis role suits engineers who enjoy:• owning systems end-to-end• building platforms others rely on• working close to production• solving reliability, scale and performance problemsYou 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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