MLOps / LLMOps Engineer,Kubernetes & MLflow

Il y a 9 heures

Arrondissement of BrusselsCapital, Brussels, Belgique Be Consultancy Group BV Temps plein

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pWe are looking for an MLOps / LLMOps Engineer for an international organization in Brussels, Belgium, with strong expertise in Machine Learning Operations, LLM infrastructure, Kubernetes and MLflow. /p pYou will manage and optimize MLOps and Large Language Model (LLM) infrastructure across on-premises and/or cloud environments, supporting scalable ML deployment, model monitoring, automation and production reliability. /p pCandidates need to be based in Europe within 2 hours of Brussels. Consultants will need to go 5 days per month on-site. European candidates are welcome to apply, but need to relocate to Brussels or within 2 hours of Brussels. /p pA work permit is required but not provided. /p h3Tasks and Responsibilities /h3 ul liManage and maintain MLOps and LLMOps infrastructure across on-premises and/or cloud environments; /li liSupport the deployment, orchestration and operation of ML and LLM workloads using Kubernetes, Docker or Podman; /li liDevelop and maintain ML pipelines and workflows using MLflow, TensorFlow Extended (TFX), Airflow or equivalent technologies; /li liAutomate infrastructure provisioning and configuration using Terraform or AWS CloudFormation; /li liImplement monitoring, logging and observability using tools such as Prometheus, Grafana, ELK Stack and OpenTelemetry; /li liSupport model testing, validation and performance monitoring in production environments; /li liWork with data pipelines, messaging systems, NoSQL databases and large-scale data environments; /li liApply security practices, support Agile delivery and maintain clear technical documentation. /li /ul h3Profile /h3 ul liBachelor's or Master's degree; /li li6+ years of IT experience, including 3+ years of MLOps experience; /li liHands-on experience managing on-premises and/or cloud-based MLOps or LLM infrastructure; /li liStrong knowledge of Kubernetes, Docker or Podman, including container orchestration environments such as EKS or PKS; /li liExperience with MLflow, TensorFlow Extended (TFX) or equivalent MLOps tools, and Apache Airflow; /li liExperience with AWS or European cloud providers; /li liProficiency in Python, Unix and Bash scripting; /li liExperience with Infrastructure as Code (IaC) using Terraform or CloudFormation; /li liKnowledge of messaging technologies such as Kafka, Redis or RabbitMQ, NoSQL databases and query languages including SQL, Hive or Pig; /li liExperience with large-scale data analytics, data lakes, production model validation, monitoring tools, Agile methodologies and technical documentation. /li liKnowledge of data encryption and ML security practices would be an advantage. /li liFluent English is required. /li /ul h3Key Technologies Skills /h3 pMLOps, LLMOps, Machine Learning Operations, Kubernetes, Docker, MLflow, TensorFlow Extended, Apache Airflow, Python, AWS, Terraform, Infrastructure as Code, Prometheus, Grafana, Model Monitoring /p

MLOps / LLMOps Engineer,Kubernetes & MLflow

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MLOps / LLMOps Engineer,Kubernetes &amp; MLflow

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