AI / MLOps Architecture & Development Opportunities
Experis
- Industry Type
- Architecture, Interior Designing
- Functional Area
- Architecture, Interior Design
- Nationality
- Any
- Keywords
- Artificial Intelligence AI expertise Machine Learning Operations MLOps proficiency Experience in architecture design and development
Job Description
Experis is looking for experienced AI/ML Operations (MLOps) Architects for project and contract opportunities. The role involves architecture and development in AI and MLOps, with remote and global work options.
- Position
- AI / MLOps Architecture & Development Opportunities
- Company
- Experis
- Location
- London, United Kingdom
- Industry
- Architecture, Interior Designing
- Experience
- 1 to 20 years
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About the role: AI / MLOps Architecture & Development Opportunities
General information about this type of role, not from the employer. The employer's actual requirements may differ, so always check the job details above.
AI / MLOps Architects and Developers design and implement machine learning operations systems to support AI projects. They work in various industries, including architecture and interior design, to integrate AI technologies into design processes and project management. Their role involves collaboration with data scientists, engineers, and designers to streamline AI model deployment and maintenance.
What this role usually involves
- Design and develop MLOps pipelines for AI model deployment and monitoring.
- Collaborate with cross-functional teams to integrate AI solutions into architecture and interior design workflows.
- Ensure scalability, reliability, and security of AI systems.
- Automate data processing and model training tasks.
- Maintain and update AI infrastructure and tools.
- Troubleshoot and optimize AI system performance.
Skills employers usually look for
- Knowledge of machine learning frameworks and tools.
- Experience with cloud platforms and containerization technologies.
- Strong programming skills in languages like Python.
- Understanding of AI model lifecycle and deployment.
- Problem-solving and analytical thinking.
- Good communication and teamwork abilities.
Usual qualifications
- A degree in computer science, software engineering, or a related field.
- Training or certification in machine learning and MLOps.
- Experience with AI and data engineering concepts.
- Familiarity with architecture or design industry tools is a plus.
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