

Cititec Talent
Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a 6-month contract in London, offering £850/day. Key skills include strong Python development, experience with LLMs, REST APIs (FastAPI), and containerization. Familiarity with MCP and agentic reasoning is essential.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
850
-
🗓️ - Date
May 9, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
On-site
-
📄 - Contract
Inside IR35
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#Deployment #ML (Machine Learning) #Python #REST (Representational State Transfer) #REST API #Documentation #API (Application Programming Interface) #FastAPI #Kubernetes #AI (Artificial Intelligence)
Role description
Machine Learning/AI Engineer | £850/day Inside IR35 | 6-month initial contract | London
Industry: Technology
Location: London
Job Type: Contract - 6-month initial
This programme delivers a production-grade enterprise agentic AI platform, with MCP as the extensibility layer.
Responsibilities
• Design and build MCP servers and tools that expose enterprise systems and workflows to AI agents.
• Implement Skills that combine tools, data, and reasoning into structured, repeatable, and governed workflows.
• Contribute to the internal AI assistant’s agentic framework, including planning, tool invocation, and orchestration logic.
• Develop secure API wrappers for systems that lack appropriate authentication, authorisation, or entitlement mechanisms.
• Work closely with product engineering teams in a “build-for” model, transferring knowledge and establishing reusable engineering patterns.
• Shape the developer experience for MCP and Skills, including templates, contribution standards, and documentation.
• Collaborate with Quality Engineering and SRE teams to ensure solutions meet requirements for reliability, governance, and operational readiness.
Skills & Experience Required
• Strong Python development experience in production environments.
• Hands-on experience with LLMs, agent frameworks, and agentic reasoning patterns.
• Practical understanding of Model Context Protocol (MCP), including tool and server design patterns.
• Experience building REST APIs, ideally using FastAPI.
• Familiarity with prompt engineering and retrieval-augmented generation (RAG) architectures.
• Experience with containerisation and Kubernetes-based deployment environments.
• Ability to operate across platform, product, and governance boundaries in large enterprise settings.
Machine Learning/AI Engineer | £850/day Inside IR35 | 6-month initial contract | London
Industry: Technology
Location: London
Job Type: Contract - 6-month initial
This programme delivers a production-grade enterprise agentic AI platform, with MCP as the extensibility layer.
Responsibilities
• Design and build MCP servers and tools that expose enterprise systems and workflows to AI agents.
• Implement Skills that combine tools, data, and reasoning into structured, repeatable, and governed workflows.
• Contribute to the internal AI assistant’s agentic framework, including planning, tool invocation, and orchestration logic.
• Develop secure API wrappers for systems that lack appropriate authentication, authorisation, or entitlement mechanisms.
• Work closely with product engineering teams in a “build-for” model, transferring knowledge and establishing reusable engineering patterns.
• Shape the developer experience for MCP and Skills, including templates, contribution standards, and documentation.
• Collaborate with Quality Engineering and SRE teams to ensure solutions meet requirements for reliability, governance, and operational readiness.
Skills & Experience Required
• Strong Python development experience in production environments.
• Hands-on experience with LLMs, agent frameworks, and agentic reasoning patterns.
• Practical understanding of Model Context Protocol (MCP), including tool and server design patterns.
• Experience building REST APIs, ideally using FastAPI.
• Familiarity with prompt engineering and retrieval-augmented generation (RAG) architectures.
• Experience with containerisation and Kubernetes-based deployment environments.
• Ability to operate across platform, product, and governance boundaries in large enterprise settings.






