Mlops Engineer

Deloitte - Recruitment; Greater London; Hybrid; GBP 64,000 - 84,000; Full time

Job summary

Deloitte is seeking an experienced MLOps Engineer for a London-based contract role with hybrid work. You will design, deploy and scale production AI solutions, covering ML pipelines, RAG systems and agent architectures across AWS/Azure.

You will collaborate with engineering, product and business teams to deliver secure, compliant, and high-performing AI capabilities in a regulated financial services environment.

Qualifications

• Strong hands-on experience in MLOps or production AI development.
• Proficiency in Python and deploying ML models in production.
• Experience building end-to-end ML pipelines: feature engineering, training, deployment, monitoring.
• Practical experience with Generative AI, LLMs, RAG and AI agent architectures.

Responsibilities

• Design and deploy production-ready AI agents and copilot solutions.
• Build RAG systems with knowledge graphs and vector search.
• Develop agent memory and context management for secure AI interactions.
• Build scalable ML training and inference pipelines using Databricks.
• Develop and productionise predictive ML models for propensity scoring and cross-selling.
• Implement batch and real-time inference with performance and explainability.
• Create AI evaluation frameworks with automated testing and monitoring.
• Integrate enterprise systems via Model Context Protocol and A2A communication.
• Monitor and improve AI solutions with user feedback.

Skills

MLOps

Python

Databricks

AWS/Azure

CI/CD

LLMs

RAG

APIs

Security

Agile

Tools

Databricks

Kubernetes

Snowflake

Splunk

Confluence

Bitbucket

Job description

Job Description

Role: MLOps Engineer - Contract Location: London | Hybrid - 3/4 days in client office. Industry: Financial Services / Banking Start Date: Nov 2026 Agreed Contract Rate (ACR): £308.33 per day Payroll provider: Rockford Payroll Info for Contingent Workers – Rockford Pay Daily Rate: £400 Inside IR35 Daily Rate breakdown Traditional Daily Rate: Up to £400 per day, dependent on experience Equivalent Annual Salary: £71,531.56 + £8,633.12 holiday pay

The Role

We are looking for experienced MLOps Engineers to join a leading global financial services organisation, working on cutting-edge Generative AI, machine learning and intelligent automation solutions. This is an exciting opportunity to design, develop and deploy production-ready AI agents, advanced retrieval systems and scalable machine learning pipelines within a complex enterprise environment. You will play a key role in delivering secure, reliable and high-performing AI solutions, working across MLOps, cloud infrastructure, data engineering and large language model technologies.

Key Responsibilities

• Design, develop and deploy production-ready AI agents and copilot solutions, taking ownership from initial prototype through to production.
• Build advanced retrieval-augmented generation (RAG) solutions, combining knowledge graphs, vector search and retrieval optimisation techniques.
• Develop agent memory and context management capabilities to support accurate, secure and personalised AI interactions.
• Design, build and maintain scalable machine learning training and inference pipelines using Databricks.
• Develop and productionise predictive ML models for propensity scoring, next-best-action recommendations, churn prediction and cross-selling opportunities.
• Implement batch and real-time inference solutions, optimising performance, latency and model explainability.
• Build and maintain AI evaluation frameworks, including automated testing, regression testing, hallucination detection and response quality monitoring.
• Develop multi-agent workflows and integrate enterprise systems using Model Context Protocol (MCP) and agent-to-agent (A2A) communication.
• Monitor production AI solutions, incorporating user feedback to improve model performance, retrieval accuracy and reliability.
• Deploy and manage AI/ML applications across AWS and/or Azure cloud environments.
• Ensure solutions meet enterprise security, governance, model risk and regulatory requirements.
• Collaborate with engineering, product and business stakeholders to deliver scalable AI solutions.

Experience & Skills Required

• Strong hands-on experience in MLOps, machine learning engineering or production AI development.
• Proficiency in Python and experience developing, deploying and maintaining machine learning models in production.
• Experience building and managing end-to-end ML pipelines, including feature engineering, model training, deployment and monitoring.
• Practical experience with Generative AI, Large Language Models (LLMs), RAG and AI agent architectures.
• Experience working with Databricks and large-scale data processing frameworks.
• Strong understanding of vector databases, embeddings, retrieval techniques and model evaluation.
• Experience developing APIs and integrating AI/ML solutions with enterprise systems.
• Hands-on experience with AWS and/or Azure cloud environments.
• Knowledge of CI/CD, automated testing, containerisation and production deployment practices.
• Strong understanding of model performance monitoring, observability, security and operational resilience.
• Experience working within Agile development environments and collaborating with cross-functional teams.

Nice to Have

• Experience with Graph RAG, knowledge graphs and advanced retrieval architectures.
• Knowledge of agent memory frameworks, including episodic and semantic memory.
• Hands-on experience with Model Context Protocol (MCP) and Agent-to-Agent (A2A) frameworks.
• Experience with LLM evaluation techniques, LLM-as-a-judge, groundedness testing and hallucination detection.
• Familiarity with Snowflake, Kubernetes, Splunk, Confluence and Bitbucket.
• Experience building recommendation engines, propensity models or next-best-action solutions.
• Knowledge of online experimentation, A/B testing and feedback-driven model optimisation.
• Experience with model governance, explainability, risk controls and responsible AI.
• Previous experience within financial services, investment banking, payments or another highly regulated environment.

Connect to your career at Deloitte

Deloitte drives progress. Using our vast range of expertise, we help our clients' become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more.

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