AI/ML Engineer

Location: Manchester, Leeds, Bristol or London (Hybrid - 2 days per week onsite)

Contract: 12 Months Initial Contract

Start Date: ASAP

We are seeking an experienced AI/ML Engineer to join a high-profile engineering team delivering cutting-edge Artificial Intelligence and Machine Learning solutions at scale. This is an exciting opportunity to work on the design, deployment and optimisation of next-generation AI platforms, helping to bring advanced ML and Generative AI capabilities into production environments.

You will play a key role in developing scalable machine learning pipelines, productionising models, and building robust MLOps frameworks that support enterprise-grade AI solutions.

Key Responsibilities

• Design, build and maintain scalable machine learning and agentic AI pipelines.
• Collaborate closely with Data Scientists to transform models and prototypes into production-ready solutions.
• Deploy, monitor and manage AI/ML models in cloud-based environments.
• Optimise model performance, scalability, reliability and cost efficiency.
• Implement model monitoring, drift detection and observability frameworks.
• Develop and maintain CI/CD pipelines for AI/ML workloads.
• Support canary, shadow and A/B testing deployment strategies.
• Build and manage feature stores and model registries.
• Troubleshoot and resolve issues across AI platforms and production environments.
• Contribute to engineering best practices, reusable frameworks and automation tooling.

Required Skills & Experience

• Experience with Unisys mainframe.
• Strong commercial experience in AI/ML Engineering or MLOps Engineering roles.
• Hands-on experience with PyTorch.
• Deep understanding of Large Language Models (LLMs) and transformer architectures.
• Experience designing and implementing Agentic AI frameworks, including approaches such as ReAct.
• Strong knowledge of Retrieval-Augmented Generation (RAG) architectures.
• Experience packaging and serving models using containers and Kubernetes-based platforms.
• Expertise with model deployment technologies such as KServe and/or Vertex AI Endpoints.
• Experience building CI/CD pipelines for machine learning workloads.
• Knowledge of model monitoring, drift detection and ML observability tooling.
• Experience with Docker and cloud-native databases.
• Familiarity with GPU-enabled environments and autoscaling strategies.
• Feature stores and model registries.
• Cost optimisation of AI workloads.
• A/B testing and production experimentation frameworks.
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently and within cross-functional teams.
• Passion for learning and keeping up to date with emerging AI technologies.
• Experience in banking & financial services industry.

What's On Offer?

• 12-month contract with long-term project potential.
• Hybrid working model with multiple UK office locations.
• Opportunity to work on enterprise-scale AI and Generative AI initiatives.
• Collaborative engineering environment with modern tooling and technology.

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