MLOps Engineer

As an MLOps Engineer at RevoData, you will help clients automate and streamline the deployment, monitoring, and maintenance of machine learning models at scale. You’ll combine strong technical skills with a collaborative mindset to build robust, scalable ML platforms that accelerate business value.

• End-to-end ML model lifecycle experience (development to decommissioning) on at least 4 production projects.
• Proficiency in deploying traditional ML & deep learning models (e.g. TensorFlow, PyTorch), and GenAI tools (e.g. LangChain, LlamaIndex, Pydantic AI). 
• Familiarity with MLflow, including experiment tracking, artifact management, and model registry. 
• Experience integrating Databricks into ML workflows, including model serving endpoints and Databricks Asset Bundles for CI/CD automation. 
• A focus on automating end-to-end ML workflows using Databricks, ensuring robustness, traceability, and team collaboration. 
• Working knowledge of LLMs, RAG, and context engineering, with practical experience using platforms such as Hugging Face, Azure AI, and OpenAI. 
• Experience using big data frameworks to build scalable pipelines for model training and inference. 
• Ability to manage priorities across diverse client projects, with a passion for learning and sharing knowledge. 
• Proficiency in Dutch is required, with exceptions for candidates with exceptional Databricks expertise (e.g., Champions or those with proven advanced experience on the platform). 

This role is open to Senior and Principal level candidates. For corresponding salary details, please see the Additional Info section at the bottom of this vacancy!