AI Solutions Architect
SKILLS
FULL DESCRIPTION
Summary
Architecting end-to-end AI/ML solutions, collaborating with stakeholders, designing scalable data pipelines, guiding teams through the ML lifecycle, selecting appropriate algorithms, and ensuring compliance and reliability of AI systems.
Key Responsibilities:
- Architecting end-to-end AI/ML solutions from concept to production
- Collaborating with stakeholders to define AI strategies aligned with business goals
- Designing scalable data pipelines, model deployment frameworks, and cloud-based AI systems
- Guiding teams through the full ML lifecycle – from data acquisition to inference
- Selecting appropriate algorithms, tools, and technologies for specific use cases
- Ensuring compliance, performance, and reliability of AI systems in production
Core Requirements:
- Strong experience in AI/ML system architecture and solution design
- Proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), and cloud platforms (AWS, Azure, GCP)
- Solid understanding of MLOps, APIs, and containerization (Docker, Kubernetes)
- Ability to lead technical teams and engage with both engineering and business stakeholders
- Track record of delivering successful AI solutions at scale
- Degree in Computer Science, Engineering, AI, or a related field (MSc or PhD preferred)
AI Solutions Architect
By DEVITECHNOLOGIES / 2 May 2025
- Full Time
- United Kingdom (Remote/Hybrid Options Available)
- Posted 3 months ago
- Competitive, aligned with top industry standards GBP / Year
Website
[Employer hidden — view at passion-project.co.uk]
What You’ll Be Working On:
Architecting end-to-end AI/ML solutions from concept to production
Collaborating with stakeholders to define AI strategies aligned with business goals
Designing scalable data pipelines, model deployment frameworks, and cloud-based AI systems
Guiding teams through the full ML lifecycle – from data acquisition to inference
Selecting appropriate algorithms, tools, and technologies for specific use cases
Ensuring compliance, performance, and reliability of AI systems in production
What We’re Looking For:
Strong experience in AI/ML system architecture and solution design
Proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), and cloud platforms (AWS, Azure, GCP)
Solid understanding of MLOps, APIs, and containerization (Docker, Kubernetes)
Ability to lead technical teams and engage with both engineering and business stakeholders
Track record of delivering successful AI solutions at scale
Degree in Computer Science, Engineering, AI, or a related field (MSc or PhD preferred)
To apply for this job email your details to [contact hidden]