AI Engineer Architect

AI Engineer Architect needs 8 years AI/ML development experience

AI Engineer Architect requires:

Knowledge and implementation experience of AI/ML in AWS Cloud services;

Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python);

DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.

Bachelors Degree in a related field (Computer Science, AI/ML).

Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python).

DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.

AI Architecture - data management, governance, model building and deployment

Knowledge and implementation experience of AI/ML in AWS Cloud services

APIs, Apigee, Developer Portals. Expertise in JSON, RESTful services, and similar related tech

Containers: Docker, Kubernetes, OpenShift, Ansible, Nexus, Software defined networking.

AI Engineer Architect duties:

Collaborate with data scientists and other AI professionals

Define the feasibility of use cases along with architectural design for the AI platform

Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools.

Work with Business and delivery partners to understand future requirements and implications for architecture