+3 years of higher education after secondary school (Bachelor or equivalent)
+9 years of IT experience
+3 projects with AI/ML solutions
+3 projects with AI/ML governance
At least one project using data science and predictive analytics
At least one project in a government environment
Requirements:
Identify and document the as-is situation
Identify and document requirements applicable
Leverage market trends and best practices
Provide architecture and ICT management recommendations
Job description
This is a remote position.
For an European Institution in The Hague, we’re currently looking for a Full Remote AI/ML Architect. As Artificial Intelligence / Machine Learning Architect, you identify and document the as-is situation and provide architecture and ICT management with recommendations on the approach to be taken. First week, onboarding will take place in the Netherlands.
Candidates need to be based in Europe and have a workpermit. Workpermits are not provided. EU Candidates need to be fluent in English. This position is open for employees and freelancers.
Description:
Identify and document the as-is situation at the Agency for AI/ML powered solutions;
Identify and document requirements applicable;
Leverage market trends, best practices and available toolkits/solutions to devise, document and propose an approach for the SDLC of these solutions;
Provide architecture and ICT management with recommendations on the approach to be taken;
Profile:
+3 years of higher education after secondary school (Bachelor or equivalent);
+9 years of IT experience on new methods and solutions;
+3 projects where AI and specifically ML powered solutions are devised, designed, built and deployed;
+3 projects where AI and ML solution governance (policies, SDLC steps, QA work) has been conducted by the consultant;
At least one project where data science and predictive analytics have been used;
At least one project in a government environment with high security and compliance requirements;
Good knowledge of AI and ML methodologies;
Good knowledge of AI and ML development/testing/deployment frameworks and toolkits (ex PyTorch, H2O, etc.);
Good knowledge of AI and ML data processing steps (data preparation, feature engineering, ML modelling, etc.);
