ML Operations Engineer

Squareone; United Kingdom; Hybrid; GBP 111,000 - 185,000; Full time

Job summary

Square One Resources Limited is seeking a Machine Learning Operations Engineer for a hybrid, two-month contract starting in November. The role focuses on building, deploying, and managing enterprise AI and Copilot solutions for a Financial Services client, spanning ML pipelines, agent orchestration, and AI governance.

FinServ experience is highly desirable. The candidate will design AI Copilot agents, develop RAG capabilities, implement memory/context management, and oversee end-to-end ML

Qualifications

• Production-grade ML deployment experience.

Responsibilities

• Design, build and deploy AI Copilot agents from development through to production.
• Develop advanced RAG and Graph RAG solutions combining vector search and knowledge graphs.
• Implement agent memory and context management to support persistent, context-aware interactions.
• Build and maintain machine learning training, batch and real-time inference pipelines.
• Integrate enterprise systems and data sources using MCP servers and agent-to-agent (A2A) communication.
• Develop AI evaluation frameworks, regression testing and human review processes.
• Monitor model performance, answer quality and production feedback to drive continuous improvement.
• Maintain model documentation, testing evidence and governance controls.
• Work with business and technical stakeholders to translate requirements into production-ready AI solutions.

Skills

Python

Databricks

MLOps

CI/CD

Model monitoring

LLMs

RAG

Graph RAG

Vector search

MCP integrations

Kubernetes

Snowflake

Data platforms

AI governance

Stakeholder mgmt

Job description

ML Operations Engineer
Hybrid - Regional Offices
Inside IR35
November start
Contract - 2 Months

Machine Learning Operations Engineer to build, deploy and manage enterprise AI and Copilot solutions for a Financial Services client. The role will focus on machine learning models, developing AI agents and retrieval systems, and delivering scalable GenAI capabilities. You will work across ML pipelines, agent orchestration, enterprise data integrations and AI governance. Financial Services experience is preferred.

Key Responsibilities:

• Design, build and deploy AI Copilot agents from development through to production.
• Develop advanced RAG and Graph RAG solutions combining vector search and knowledge graphs.
• Implement agent memory and context management to support persistent, context-aware interactions.
• Build and maintain machine learning training, batch and real-time inference pipelines.
• Integrate enterprise systems and data sources using MCP servers and agent-to-agent (A2A) communication.
• Develop AI evaluation frameworks, regression testing and human review processes.
• Monitor model performance, answer quality and production feedback to drive continuous improvement.
• Maintain model documentation, testing evidence and governance controls.
• Work with business and technical stakeholders to translate requirements into production-ready AI solutions.

Essential Skills and Experience:

• Experience developing and deploying machine learning models in production environments.
• Hands-on experience building AI agents, Copilot solutions and Generative AI applications.
• Strong Python development skills and experience with Databricks.
• Expertise in MLOps, CI/CD, model monitoring and lifecycle management.
• Experience with LLMs, RAG, Graph RAG and vector search.
• Knowledge of batch and real-time inference pipelines.
• Experience with MCP integrations and agent orchestration.
• Familiarity with Kubernetes, Snowflake and enterprise data platforms.
• Understanding of AI security, governance, evaluation and observability.
• Strong stakeholder management and communication skills.
• Financial Services experience is highly desirable.

Disclaimer

Notwithstanding any guidelines given to level of experience sought, we will consider candidates from outside this range if they can demonstrate the necessary competencies. Square One embraces diversity and will treat everyone equally. Please see our website for our full diversity statement.