Machine Learning Engineer in Manchester, Greater Manchester

The Opportunity

A leading financial consultancy is seeking a Senior AI & ML Engineer to lead the design, development and deployment of cutting-edge AI, Machine Learning and Generative AI solutions. You'll play a key role in shaping technical strategy, building production-grade AI systems and driving engineering best practices across complex client engagements.

Key Responsibilities

• Lead the design and delivery of AI, Machine Learning, Agentic AI and RAG-based solutions.
• Build and deploy production-grade models using Python, PyTorch and modern transformer architectures.
• Design scalable MLOps frameworks, CI/CD pipelines and model deployment strategies.
• Develop model serving capabilities using cloud-native technologies and containerised environments.
• Create reusable frameworks, tooling and templates to accelerate AI adoption.
• Drive model monitoring, drift detection, testing and governance best practices.
• Collaborate with architects, data scientists, platform engineers and stakeholders to deliver business value.
• Mentor and coach engineers while promoting engineering excellence across teams.
• Support technical strategy, research and innovation initiatives.

What We're Looking For

• Extensive experience in AI Engineering, Machine Learning Engineering or Applied AI.
• Expert-level Python and PyTorch skills.
• Strong understanding of LLMs, transformer architecture and model optimisation.
• Experience designing and deploying RAG solutions and AI agents.
• Strong cloud experience, ideally within Google Cloud Platform (GCP).
• Experience with Docker, Kubernetes and modern MLOps tooling.
• Proven experience taking AI solutions from concept to production at scale.
• Strong communication skills with both technical and business stakeholders.
• Experience leading technical design and mentoring engineers.

Desirable Experience

• Financial services or regulated industry experience.
• Experience within enterprise-scale AI environments.
• Knowledge of Vertex AI, KServe and MLFlow.
• Feature Store and Model Registry experience.
• Experience building internal AI platforms or reusable AI frameworks.
• Cloud certifications and advanced academic qualifications are beneficial.