Artificial Intelligence Architect
Posted Today by Stott and May
£510 Per day
Inside
Hybrid
London Area, United Kingdom
Summary: The AI / ML Architect role in London involves designing, building, and deploying advanced machine learning and AI-driven solutions. The successful candidate will leverage their extensive experience to create scalable models and integration patterns that deliver real-world value from data. This position requires a blend of technical expertise, applied ML engineering, and hands-on development. The role is hybrid, requiring two days a week on-site work.
Key Responsibilities:
- Design, build, and train end-to-end machine learning models across NLP, predictive analytics, classification, and computer vision use cases
- Experiment with algorithms, optimise hyperparameters, and evaluate model performance
- Collect, process, and prepare structured and unstructured datasets for model training and validation
- Implement feature engineering, data augmentation, and data quality controls
- Develop APIs, services, or microservices to integrate models into production platforms
- Deploy, monitor, and manage models using MLOps tooling, automation, and versioning practices
- Analyse performance metrics (accuracy, precision, recall, F1-score) and optimise models for scalability and efficiency
- Collaborate with product teams, engineers, and data scientists to translate business requirements into technical solutions
- Document architectures, workflows, and methodologies to ensure reproducibility and maintainability
- Stay current on emerging AI technologies including generative models, reinforcement learning, and transformer-based architectures
Key Skills:
- 10+ years software engineering experience, including 5+ years in applied AI/ML
- Advanced proficiency in Python, PyTorch, TensorFlow, and modern NLP frameworks
- Hands-on experience with LLMs, transformer architectures, LangChain, and Hugging Face
- Strong knowledge of algorithms, machine learning lifecycles, and model evaluation techniques
- Deep understanding of BFSI environments including risk, compliance, and AML/KYC
- Practical experience with cloud platforms (AWS/Azure/GCP) and containerisation (Docker/Kubernetes)
- Experience building scalable ML systems and secure, production-grade applications
- Proven ability to work collaboratively in cross-functional teams
- Strong communication skills with the ability to present technical concepts to non-technical stakeholders
- Demonstrated ability to write clear documentation and apply engineering best practices
Salary (Rate): £510 daily
City: London
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
AI / ML Architect
Location: London (Hybrid – 2 days/week onsite)
Duration: 6 months
Day Rate: £510 per day (Inside IR35)
Role Overview
We are seeking an experienced AI / ML Architect to design, build, and lead the deployment of advanced machine learning and AI-driven solutions. The successful consultant will enable real-world value from data by architecting models, pipelines, and integration patterns that scale across the organisation. This role combines technical depth, applied ML engineering, solution design, and hands-on development.
Key Responsibilities
- Design, build, and train end-to-end machine learning models across NLP, predictive analytics, classification, and computer vision use cases
- Experiment with algorithms, optimise hyperparameters, and evaluate model performance
- Collect, process, and prepare structured and unstructured datasets for model training and validation
- Implement feature engineering, data augmentation, and data quality controls
- Develop APIs, services, or microservices to integrate models into production platforms
- Deploy, monitor, and manage models using MLOps tooling, automation, and versioning practices
- Analyse performance metrics (accuracy, precision, recall, F1-score) and optimise models for scalability and efficiency
- Collaborate with product teams, engineers, and data scientists to translate business requirements into technical solutions
- Document architectures, workflows, and methodologies to ensure reproducibility and maintainability
- Stay current on emerging AI technologies including generative models, reinforcement learning, and transformer-based architectures
Profile & Required Expertise
10+ years software engineering experience, including 5+ years in applied AI/ML
Advanced proficiency in Python, PyTorch, TensorFlow, and modern NLP frameworks
Hands-on experience with LLMs, transformer architectures, LangChain, and Hugging Face
Strong knowledge of algorithms, machine learning lifecycles, and model evaluation techniques
Deep understanding of BFSI environments including risk, compliance, and AML/KYC
Practical experience with cloud platforms (AWS/Azure/GCP) and containerisation (Docker/Kubernetes)
Experience building scalable ML systems and secure, production-grade applications
Proven ability to work collaboratively in cross-functional teams
Strong communication skills with the ability to present technical concepts to non-technical stakeholders
Demonstrated ability to write clear documentation and apply engineering best practices
Desirable Experience
Ability to align ML strategies with long-term business and platform objectives
Familiarity with emerging trends in generative AI, RAG workflows, or reinforcement learning
Experience influencing architecture decisions at enterprise scale