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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Multimodal Data Engine Expert - **Company:** Eu Recruit - **Location:** Amsterdam, Netherlands - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, Cloud Computing, Databases, Microprocessors, Distributed Data Store, Distributed Systems, Natural Language Processing, Performance Tuning, Systems Integration, Reinforcement Learning, Graphics Processing Unit (GPU), Data Storage Management, High Performance Computing, Large Language Models, Data Management - **Published:** September 3, 2026 - **Apply:** https://eu-recruit.com/jobs/multimodal-data-engine-expert/#vacancy-apply ## About the Role * Strong programming skills in one or more languages such as C, C++, Python or Java. * Strong technical background in areas such as: + Database systems + Big data platforms + Distributed systems + High-performance computing * Practical or research experience working with core systems components such as: + Query optimisers + Query execution engines + Storage engines + Distributed storage systems * Strong understanding of heterogeneous computing architectures involving CPUs, GPUs and NPUs. * Experience with heterogeneous resource management, scheduling and performance optimisation. * Ability to design systems that efficiently utilise large-scale compute resources. * Experience developing, operating or maintaining cloud-computing platforms. * Familiarity with modern DevOps and infrastructure engineering practices. Preferred Experience * Experience with LLM fine-tuning and reinforcement learning. * Knowledge of multimodal AI technologies including: + Natural language processing + Computer vision + Time-series processing * Experience integrating AI technologies with database or data-management systems. * Experience developing infrastructure for large-scale AI, multimodal or agent-based workloads. * Strong understanding of performance engineering, scalability and distributed system design. ## Description The role will focus on the architecture and development of an advanced multimodal data platform supporting heterogeneous computing, multimodal processing, vector storage, distributed caching, AI-enhanced database technologies and intelligent data agents. You will help build end-to-end capabilities for processing and managing large-scale heterogeneous and unstructured data, covering compute scheduling, data processing, retrieval, storage and autonomous system management. The objective is to develop high-performance data infrastructure optimised for large language models, multimodal AI workloads and emerging AI agent ecosystems., Multimodal Data Processing Platform * Design and develop a unified platform for scheduling and managing heterogeneous compute resources including CPUs, GPUs and NPUs. * Develop serverless resource pooling capabilities across multiple compute engines. * Improve heterogeneous resource scheduling, workload placement and overall infrastructure utilisation. * Support scalable deployment of data-processing workloads across distributed environments. Multimodal Computing Engines * Design and optimise processing engines for large-scale structured, unstructured and multimodal data. * Support efficient processing of text, images, video and other data formats. * Develop next-generation query optimisation and hybrid execution techniques. * Enable high-performance retrieval and processing across vector, textual, geospatial and other data types. Vector Storage and Indexing * Design scalable systems for multimodal vector storage, retrieval and indexing. * Develop capabilities for metadata management, access control and index lifecycle management. * Integrate with relevant open-source data and AI ecosystems. * Improve storage efficiency, data placement and retrieval performance for AI workloads. Distributed Caching * Design high-performance distributed caching services for multimodal data platforms. * Provide low-latency near-compute caching for processing engines. * Improve data movement and sharing between distributed compute engines. * Optimise end-to-end performance across large-scale multimodal data pipelines. AI-Powered Data Agents * Apply AI4DB, large language models and agent technologies to develop intelligent data-management capabilities. * Build agents and reusable skills that automate data processing, workload development, storage management, analytics and system operations. * Explore autonomous optimisation and decision-making within database and data infrastructure. * Integrate AI capabilities directly into data-management workflows. ## Related Videos - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Focoos AI: Building the Future of Computer Vision](https://www.wearedevelopers.com/videos/1659-focoos-ai-building-the-future-of-computer-vision) - [Green Cloud Computing](https://www.wearedevelopers.com/videos/592-green-cloud-computing) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Computer Vision from the Edge to the Cloud done easy](https://www.wearedevelopers.com/videos/263-computer-vision-from-the-edge-to-the-cloud-done-easy) - [Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML ](https://www.wearedevelopers.com/videos/78-leverage-cloud-computing-benefits-with-serverless-multi-cloud-ml) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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