{"id":2632901,"url":"https://alion.io/job/cronos-europa-mlops-llmops-engineer-senior","title":"MLOps / LLMOps Engineer Senior","company":{"id":691250,"name":"Cronos Europa","domain":"cronoseuropa.com","url":"https://alion.io/company/cronoseuropa","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Brussels, Belgium"],"countries":["BE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":75000,"max_usd":192000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2102},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Bash","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Podman","optional":false},{"name":"Python","optional":false},{"name":"RabbitMQ","optional":false},{"name":"Redis","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Unix","optional":false},{"name":"Amazon CloudWatch","optional":true},{"name":"Grafana","optional":true},{"name":"OpenSearch","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Prometheus","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-10-15T13:58:05Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-17T21:27:32Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About Cronos Europa\nCronos Europa is a leading IT and digital transformation partner dedicated exclusively to European Institutions and agencies, delivering mission-critical solutions that shape Europe's digital future. As part of the Cronos Group, one of the most innovative and fastest-growing tech ecosystems in Europe, we benefit from a vast pool of expertise and cutting-edge capabilities. With over 1,000 specialists across Belgium, Luxembourg, and the Netherlands, we combine deep institutional knowledge with strong engineering excellence to support long-term, high-impact EU programmes requiring reliability, scalability, and innovation.\nAbout the job\nWe are looking for an MLOps / LLMOps Engineer to design, deploy, monitor and optimise production-grade machine learning and large language model systems within secure hybrid on-premise and cloud environments. The role combines ML engineering, infrastructure automation, containerisation, security awareness and close collaboration with data science and backend development teams.\nResponsibilities\nDesign, build, and maintain production-grade ML systems with a strong focus on Large Language Models (LLMs) in a secure hybrid on-prem / cloud infrastructure. \nDeploy, test, manage and monitor ML models in different containerised environments. \nWork closely with data scientists and back-end developers to build, test, integrate and deploy ML models. \nEvolve the LLMOps lifecycle: data preparation, fine-tuning, evaluation, deployment, monitoring, and iteration. Develop evaluation frameworks for LLM quality, robustness, and regression tracking. \nAnalyse performance metrics and troubleshoot issues to ensure high availability and reliability. \nDesign CI/CD pipelines, use orchestration solutions and data versioning tools. \nCreating automated anomaly detection systems and constant tracking of its performance and optimising ML pipelines for scalability, efficiency and cost-effectiveness. \nProvision of security studies, security assessments or other security matters associated with information system projects. \nProvision of support and guidance to other team members on LLMOps/MLOps practices. \nSpecific expertise\nExcellent knowledge of managing an on-prem and/or cloud LLM / MLOps infrastructure. \nExcellent knowledge of containerisation and orchestration platforms (e.g. Kubernetes, Docker, Podman, EKS, PKS). Good knowledge of MLflow, TensorFlow (TFX) or equivalents. \nGood knowledge of Airflow. \nGood knowledge of AWS or EU cloud providers. \nGood knowledge of Python. \nGood knowledge of Unix and Bash. \nGood knowledge agile software development methodologies. \nGood knowledge of infrastructure as code (Terraform, CloudFormation). \nGood knowledge of messaging services and platforms (e.g. Kafka, Redis, RabbitMQ). \nKnowledge of data security measures (knowledge of encryption mechanisms and ML security is considered a plus). \nKnowledge of NoSQL databases, such as OpenSearch, MongoDB, etc. \nKnowledge of query languages, such as SQL, Hive, Pig, etc. and with information extraction. \nExperience with data analytics over big datasets, non-structured databases as well as data lakes. \nExperience with monitoring and logging tools (e.g. ELK stack, Prometheus, Grafana, OpenTelemetry, Cloudwatch). \nExperience with model testing and model validation in production environments. \nAbility to write clear and structured technical documentation. \nGood knowledge of European Commission grant management ecosystem (eGrants) would be an asset. \nEQF Level 6 or higher in a relevant field such as Computer Science, Information Technology, or Systems Engineering. \nSkills and competencies\nStrong problem-solving and analytical skills. \nStrong organisational and time-management skills. \nStrong team spirit and experience working effectively within a collaborative team. \nCapability of integration in an international/multi-cultural environment. \nExcellent communication skills to articulate complex technical concepts. \nAttention to detail in infrastructure design and well-structured documentation. \nAbility to write clean, efficient, and maintainable code. \nIf you wish to integrate a dynamic structure on a human scale while working with the latest technologies, don't wait anymore and join 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