J

Machine learning solution architect

Jobster

Permanent
2 maanden geleden
Elektromonteur duurzame energietechniek

Elektromonteur duurzame energietechniek

Eminent

Permanent
ongeveer 1 maand geleden
Audiovisueel monteur

Audiovisueel monteur

Eminent

Permanent
ongeveer 1 maand geleden
Paneelbouwer

Paneelbouwer

Eminent

Permanent
ongeveer 1 maand geleden
Project engineer automatisering

Project engineer automatisering

Eminent

Permanent
ongeveer 1 maand geleden
Elektromonteur e&i

Elektromonteur e&i

Eminent

Permanent
ongeveer 1 maand geleden
Leidinggevend elektromonteur / voorman

Leidinggevend elektromonteur / voorman

Eminent

Permanent
ongeveer 1 maand geleden
Service technicus e&i

Service technicus e&i

Eminent

Permanent
ongeveer 1 maand geleden
Software (automation) engineer e&i

Software (automation) engineer e&i

Eminent

Permanent
ongeveer 1 maand geleden
Leidinggevend elektromonteur e&i

Leidinggevend elektromonteur e&i

Eminent

Permanent
ongeveer 1 maand geleden
Elektromonteur e&i

Elektromonteur e&i

Eminent

Permanent
ongeveer 1 maand geleden
J

Machine learning solution architect

Jobster Den Haag (2490)

Contract: PermanentUren: Salaris:

Job description

Job Title: Machine Learning Solution ArchitectJob Type: PermanentJob Location: Hague, NetherlandsLanguage: Dutch ProficiencyJob Description:The ML architect will be responsible for designing the overall MLOps architecture and ensuring its alignment with clients business objectives.Define and design the end-to-end architecture for MLOps pipelines, ensuring scalability, reliability, and security.Establish a modular architecture that supports continuous integration and continuous deployment (CI/CD) of machine learning applications.Identify and select the appropriate tools, frameworks, and platforms for model development, deployment, and monitoring (e.g., Kubeflow, MLflow, TensorFlow, SageMaker).Work closely with business stakeholders to translate requirements into scalable machine learning solutions.Act as the technical liaison between MLOPs teams and business units, ensuring alignment with project goals and timelines.Facilitate the transition from development to production, ensuring models are deployed with minimal friction.Design observability and monitoring frameworks to detect drift, ensure performance, and trigger automated re-deployments when necessary.Define standards, best practices, and guidelines for MLOps, ensuring adherence to compliance and regulatory requirements.Collaborate with data engineers, data scientists, DevOps engineers, and other stakeholders to implement best practices for model lifecycle management.Develop strategies for deploying ML models as APIs, batch processing jobs, or streaming services. #J-18808-Ljbffr