MLOps Engineer

pI’m working with an established organisation in Antwerp that is investing heavily in its internal AI capabilities and building a new benterprise AI platform /b. /p pThe platform will give employees and engineering teams a secure environment to build, deploy, and use AI solutions based on internal company knowledge and data. /p pAs their AI engineering function continues to grow, they are looking for an MLOps / AI Platform Engineer with at least 3 years’ professional experience across MLOps, DevOps, Platform Engineering, or AI infrastructure. /p h3The Role /h3 pYou’ll work at the intersection of bAI engineering, MLOps and infrastructure /b, helping build and operate the infrastructure layer supporting the wider AI platform. /p pThe environment combines bOpenShift, Kubernetes, LLM workloads, observability, security and on-premise infrastructure /b. /p pYou’ll be involved in everything from container environments and monitoring through to secure AI workloads and the infrastructure required to run models internally. /p h3Key Responsibilities /h3 ul liConfigure and manage bOpenShift environments /b, including namespaces, network policies and resource allocation. /li liBuild and maintain monitoring, observability and alerting across the AI platform. /li liWork with technologies including bElastic, Prometheus, Grafana and LangSmith /b. /li liEstablish visibility across LLM workloads, including prompts, token usage, latency and evaluation. /li liIntegrate platform logging with centralised logging and bSIEM environments /b. /li liHelp design and prepare bGPU infrastructure /b for on-premise model inference. /li liSupport GPU scheduling, capacity planning and infrastructure requirements as AI usage grows. /li liBuild secure and isolated environments for executing AI workloads. /li liTake ownership of operational readiness, including bbackup and recovery procedures, runbooks and on-call processes /b. /li liAutomate infrastructure and operational processes using bPython or Go /b. /li liCollaborate with AI engineers, platform engineers and wider infrastructure teams. /li /ul h3What They’re Looking For /h3 ul libMinimum 3 years of professional experience /b within MLOps, DevOps, Platform Engineering, Cloud/Infrastructure Engineering or a closely related position. /li liExperience working with bML or LLM workloads /b, ideally involving areas such as: /li liModel serving /li liVector databases /li liGPU workloads /li liAI/ML infrastructure /li liStrong knowledge of bKubernetes and/or OpenShift /b. /li liExperience with observability technologies such as bPrometheus, Grafana, Elastic or similar tooling /b. /li liUnderstanding of container security, including: /li liNetwork policies /li liWorkload isolation /li liPod security /li liScripting and automation experience using bPython or Go /b. /li liBachelor's or Master's degree in Computer Science or a related technical discipline. /li liFluent English. /li liDutch is a strong advantage, while French is beneficial. /li /ul h3Why Consider It? /h3 pThis is an opportunity to join an AI platform initiative at an early stage, rather than simply stepping into an established maintenance environment. /p pYou’ll have the opportunity to work across bMLOps, Kubernetes/OpenShift, LLM infrastructure, observability, platform security and GPU computing /b, helping build the technical foundations required to move AI applications securely into production. /p pThe position offers a bpermanent contract, competitive salary and benefits package /b, alongside long-term career development opportunities within an established organisation. /p