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AI Engineer
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Interex Professionals
AI Engineer
Opdrachtomschrijving
- Develop, optimise, deploy and maintain end-to-end AI/ML pipelines, from training and packaging through monitoring and lifecycle management. - Develop, test, document, refactor and maintain AI/ML components, programs and scripts. - Apply machine learning and data science to new datasets; evaluate model performance, data quality and outcomes. - Troubleshoot and improve ML models, pipelines, datasets and AI development processes. - Build and maintain data pipelines, including ETL/ELT. - Develop AI modules and integrate them into builds, validating functionality, security, quality and performance. - Support the full AI/software engineering lifecycle, including requirements, automation, testing, release, deployment and monitoring. - Implement secure and maintainable engineering practices, including MLOps/AIOps, CI/CD and automation. - Monitor AI technologies and contribute to technology assessments, roadmaps and knowledge sharing. - Report progress, risks and blockers and collaborate with technical teams.
Eisen
- Strong hands-on experience in Python, machine learning, software engineering and applied AI. - Strong understanding of ML concepts, model evaluation, performance measurement and model improvement. - Practical experience with LLMs, foundation models, Generative AI and pre-trained models. - Strong experience with RAG, embeddings, vector databases and AI application architectures. - Experience building production-grade AI agent backends, using LangChain, LlamaIndex, Pydantic AI or similar. - Strong MLOps/AIOps experience, including Git/version control, CI/CD, automation and model/experiment lifecycle management. - Experience developing REST APIs and backend services, particularly Python with FastAPI/Pydantic. - Experience with Docker, Kubernetes, Helm, cloud infrastructure and orchestration tools such as Airflow or Argo. - Experience with LLM guardrails, observabilit...
AI Engineer
Opdrachtomschrijving
- Develop, optimise, deploy and maintain end-to-end AI/ML pipelines, from training and packaging through monitoring and lifecycle management. - Develop, test, document, refactor and maintain AI/ML components, programs and scripts. - Apply machine learning and data science to new datasets; evaluate model performance, data quality and outcomes. - Troubleshoot and improve ML models, pipelines, datasets and AI development processes. - Build and maintain data pipelines, including ETL/ELT. - Develop AI modules and integrate them into builds, validating functionality, security, quality and performance. - Support the full AI/software engineering lifecycle, including requirements, automation, testing, release, deployment and monitoring. - Implement secure and maintainable engineering practices, including MLOps/AIOps, CI/CD and automation. - Monitor AI technologies and contribute to technology assessments, roadmaps and knowledge sharing. - Report progress, risks and blockers and collaborate with technical teams.
Eisen
- Strong hands-on experience in Python, machine learning, software engineering and applied AI. - Strong understanding of ML concepts, model evaluation, performance measurement and model improvement. - Practical experience with LLMs, foundation models, Generative AI and pre-trained models. - Strong experience with RAG, embeddings, vector databases and AI application architectures. - Experience building production-grade AI agent backends, using LangChain, LlamaIndex, Pydantic AI or similar. - Strong MLOps/AIOps experience, including Git/version control, CI/CD, automation and model/experiment lifecycle management. - Experience developing REST APIs and backend services, particularly Python with FastAPI/Pydantic. - Experience with Docker, Kubernetes, Helm, cloud infrastructure and orchestration tools such as Airflow or Argo. - Experience with LLM guardrails, observabilit...