DevOps Engineer

• Design, build, deploy, and monitor ML and LLM pipelines across the full model lifecycle
• Deploy production-grade ML and LLM solutions to enterprise customers
• Implement CI/CD, GitOps, containerization, and orchestration using tools such as Docker and Kubernetes
• Monitor model performance, data drift, and system health, including alerting and truth analysis
• Manage and optimize cloud infrastructure (AWS and/or Azure) for scalability and cost efficiency
• Collaborate closely with Product, DevOps, and AI research teams
• Communicate model performance and system status to technical and non-technical stakeholders

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 3+ years of experience in MLOps, ML Engineering, LLMOps, or DevOps roles
• Strong experience with public cloud platforms (AWS and/or Azure)
• Proficiency in Python and distributed ML frameworks such as Ray, DeepSpeed, FSDP, or Megatron-LM
• Solid understanding of LLM architectures, deployment patterns, and retrieval-based systems
• Experience with CI/CD pipelines, containerized environments, and Kubernetes
• Fluent English; Spanish is a plus

Preferred experience:

• Experience with Mixture-of-Experts models
• Multi-cloud or hybrid cloud environments
• Real-time or streaming ML systems
• LLM observability, inference optimization, and API management

This opportunity is with a leading European deep-tech company operating at the intersection of AI and advanced computing. The role focuses on deploying and operating large-scale machine learning and large language model systems used by global enterprise clients, including Fortune 500 companies. What is offered:

• Competitive annual salary starting from 45,000 EUR, depending on experience and qualifications
• Signing bonus upon joining and a retention bonus at contract completion
• Relocation support if applicable
• Fixed-term contract until June 2026
• Hybrid working model with flexible hours (3 days onsite, 2 days remote)
• International, highly technical environment within a fast-scaling Series B company