45 AI Engineer jobs in Netherlands available for remote work from home. Apply for positions such as Senior ML Engineer (AI Research, Physical AI), Senior ML Engineer (AI Research/ Portability), Software Engineer – AI Workflows (m/f/d) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will design, train, and evaluate large-scale models and learning algorithms for robotic agents to perceive and act in the physical world. This involves developing vision-language-action architectures and collaborating with research teams to deploy reliable systems in real-world environments.
You will design and build research prototypes and robust systems at the intersection of models, providers, and agent runtimes. Responsibilities include formulating research questions, developing evaluation methods, and turning promising results into reusable components.
You will develop and improve AI algorithms for IoT products and build automated workflows to streamline organizational processes. The role involves prototyping new solutions and integrating AI into core business systems like CRM and ERP.
You will develop and improve AI algorithms for sensor products and build automated workflows to streamline internal organizational processes. The role involves prototyping new solutions and integrating AI into core business systems like CRM, ERP, and HR.
Develop and improve AI algorithms for IoT sensor products and build automated workflows to streamline organizational processes. Integrate AI into core business systems like CRM, ERP, and HR while prototyping new infrastructure.
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Build and ship mobile features for KIRA's AI Finance Agent across Android and iOS platforms. Collaborate with product and design teams to transform complex financial journeys into intuitive mobile experiences.
Build and ship native Android features for an AI Neobank app using Kotlin and Jetpack Compose. Collaborate with product and design teams to simplify complex financial user journeys and optimize app performance.
Build and ship mobile features for an AI Neobank app across Android and iOS platforms. Collaborate with product and design teams to transform complex financial journeys into intuitive mobile experiences.
Build and ship native Android features for an AI Finance Agent using Kotlin and Jetpack Compose. Focus on optimizing app performance, integrating backend APIs, and simplifying complex financial user journeys.
Own and scale the agent layer and matching engine for an AI-first fundraising platform. This includes building conversational agents for investor outreach and managing the backend data pipelines.
Own the conversation layer of an AI fundraising platform, managing agents that handle replies, booking, and relationship nurture. Build broader applied-AI features including classification, extraction, and the evaluation framework to ensure quality.
Build AI-native systems, agents, and automation workflows to improve financial services and operational efficiency for a Neobank app. Design and implement reliable AI experiences for onboarding, KYC, and risk review while managing constraints like latency and hallucination risk.
Build and maintain core backend services, APIs, and workflows for an AI Neobank app across various financial services. Design reliable systems for transactions, partner integrations, and reconciliation while ensuring system observability and security.
Build AI-native systems, agents, and automated workflows to optimize financial services and internal operations. Design and productionize scalable AI integrations with LLMs and internal data to reduce manual work.
Build end-to-end customer-facing and internal product features for an AI Neobank app. Develop web flows, backend APIs, and operational systems across various financial services including insurance and payments.
Build and ship native Android features for an AI Neobank app using Kotlin and Jetpack Compose. Collaborate with product and design teams to optimize user journeys and integrate secure backend APIs.
Develop production-ready coding agents and agentic workflows by integrating internal and open-weight models into JetBrains products. Design the agent loop, create evaluation suites, and establish feedback loops to improve model behavior based on real-world usage.
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Set the technical direction for AI and GenAI initiatives, focusing on building production-grade LLM applications and RAG systems. Lead the productization of AI tools while ensuring reliability, cost-efficiency, and real client value.
Design and operate AI-powered services and internal tools to improve developer and operator productivity. Partner with cross-functional teams to implement secure, scalable LLM integrations and track success via productivity metrics.
Design and develop advanced agentic AI solutions capable of autonomous planning, reasoning, and task execution. Integrate RAG pipelines and multi-agent communication protocols to deliver robust end-to-end AI solutions for the financial sector.
Develop and implement AI solutions by designing proof-of-concepts and translating them into minimum viable products. Collaborate with cross-functional teams to optimize AI models and integrate capabilities into existing systems.
Evaluate and analyze LLM performance while architecting and building inference and training pipelines. You will contribute to hands-on design, model training, and deployment strategies within a technical greenfield project.
The role involves reviewing and refining AI-generated responses related to system operations, troubleshooting, and infrastructure management for technical accuracy and alignment with best practices. Responsibilities also include drafting realistic operational scenarios and assessing the AI's reasoning for logic, risk, and compliance.
The Staff Backend Engineer will shape and scale the core infrastructure behind GitLab CI, focusing on integrating AI into CI/CD workflows to enhance performance, reliability, and usability for millions of jobs. This involves defining success metrics for AI agents, building necessary instrumentation, and hardening the underlying CI pipeline execution infrastructure.
Design and implement full-stack applications and AI agents that enable rapid development and deployment. Collaborate with product, UX, and domain experts to deliver customer-focused solutions.
Conduct experiments to efficiently train large language models and explore methods of guided generation and search. Mine relevant data at web scale and conduct experiments with various reinforcement learning configurations.
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You will own the reliability, performance, and observability of the entire inference stack. This includes designing telemetry pipelines, tuning Kubernetes autoscalers, and creating automation for incident management.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate cross-functionally with product and engineering teams.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate with product and engineering teams.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate with cross-functional teams.
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