MLOPS Engineer.

We are seeking a highly skilled engineer to join our team focused on building and operating Large Language Model (LLM) services in a secure hybrid on‑premise and cloud environment. The role involves close collaboration with data scientists and backend developers to deliver reliable, scalable machine learning solutions.

Key responsibilities

• Design, build, and maintain production‑grade ML systems centered on LLMs across hybrid on‑prem/cloud infrastructure.

• Deploy, test, monitor, and manage ML models in containerised environments.

• Develop and evolve the LLMOps lifecycle, including data preparation, fine‑tuning, evaluation, deployment, and monitoring.

• Create CI/CD pipelines, orchestration solutions, and data versioning tools for ML workflows.

• Implement automated anomaly detection, performance tracking, and cost‑optimisation for ML pipelines.

Required qualifications

• Strong expertise in managing on‑premise and/or cloud LLM/MLOps infrastructure.

• Proficiency with containerisation and orchestration platforms such as Kubernetes, Docker, Podman, EKS, PKS.

• Hands‑on experience with MLflow, TensorFlow (TFX), Airflow, and major cloud providers (AWS or EU cloud).

• Solid programming skills in Python, Unix/Bash, and infrastructure‑as‑code tools like Terraform or CloudFormation.

• Familiarity with messaging systems (Kafka, Redis, RabbitMQ) and NoSQL databases (OpenSearch, MongoDB).

Nice to have

• Knowledge of encryption mechanisms and ML security best practices.

• Experience with the European Commission grant management ecosystem (eGrants).