Top AI Jobs in Manchester

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Freelance AI Engineer to design, develop, and deploy AI and machine learning solutions. Responsibilities include algorithm development, data analysis, building production-ready models, and contributing to the platform's AI initiatives in a fully remote capacity.

Hunt and build the EMEA robotics and physical AI business: execute GTM strategy, prospect and open net-new accounts, orchestrate partner ecosystems, lead complex technical-commercial programs from validation to close, run marketing and demand-generation initiatives, and represent the company at industry events. Requires technical advising with engineering teams and up to 25% travel across EMEA.

Build and scale AI-driven automation solutions using LLMs and agent frameworks. Design multi-step workflows, integrate AI with internal systems (HR, finance, legal, ticketing), automate document processing and data extraction, and train internal teams. Collaborate with technical leads, product, and IT to deliver practical, production-ready automation and iterate quickly.

Mentor apprentices on an AI Champion programme by assessing progress, supporting portfolio development and EPA preparation, providing technical advice and regular feedback, contributing to curriculum content, safeguarding learners, and liaising with employers and the Delivery Team to drive AI adoption.

Mentor apprenticeship learners to identify and implement AI-driven workflow improvements, assess progress against the apprenticeship standard, support portfolio and EPA preparation, provide technical support and mentoring sessions, report learner progress, and uphold safeguarding and equality responsibilities.

Work as a quantitative consultant delivering insight programmes that combine advanced analytics, mixed methods and AI to solve client problems. Contribute to analysis, synthesize evidence, build consultancy skills, explore AI tools, support business growth and help shape proposals and client-facing work.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The Senior AI Transformation Consultant works with clients to identify AI opportunities, define robust business cases, and oversee AI project deployments, ensuring solutions deliver value.

Lead and build Maze’s new AI-native Market Research service: define research vision and methodologies, recruit and manage a research team, own delivery quality, partner with Product/Engineering and GTM, and serve as executive research lead on strategic customer engagements.

As a Technical Lead, you will guide software engineering teams, translate client requirements into applications, ensure best practices, and shape technical direction while mentoring team members.

Design, scale, and productionize ML and physics-based scientific code for drug and materials discovery. Transition prototypes to robust products, orchestrate distributed GPU training, implement hardware optimizations, and support model lifecycle and integration into large-scale simulation frameworks.

Lead and grow a team of 5-8 AI engineers to design, build, and deploy conversational, generative, and agentic AI systems. Own delivery roadmaps, collaborate with product and platform teams, establish AI engineering best practices, build CI/CD and evaluation pipelines, and communicate technical progress and risks to senior leadership.

Lead delivery of AI-powered insights for clients, manage relationships, and drive commercial growth while innovating technical workflows.

As an AI Creative Producer, you'll develop and scale AI-generated content across various platforms, collaborate with teams, and enhance production workflows.

Lead MVP delivery of an AR-powered, culturally sensitive mobile product providing real-time Quranic recitation translation. Define scope, manage ASR/NLP and mobile teams, ensure GDPR/privacy-by-design and Sharia compliance, design reverent Prayer Mode UX, deploy cross-platform with offline/edge support, and track latency, confidence, stability, and accessibility KPIs.

Lead design and deployment of human-machine collaboration strategies, evaluate workflows for AI teaming opportunities, create shared-control frameworks, coordinate with engineers and UX, manage training/change management, measure teaming performance, ensure ethical AI integration, and produce SOPs and stakeholder documentation.

Deliver and operationalize an AI Code of Responsibility and governance for a 35-person, values-driven SME: implement interim AI guidelines, define decision rights, run workshops to protect creative boundaries, produce 3–4 implementation-ready roadmaps (Shopify integration, fabric calculators, PO/SO automation), assess environmental and privacy impacts, create training materials and an AI decision framework, and establish incident reporting and sustainable governance that the team can run independently.

Recruit experienced mid-to-senior AI/ML engineers and data scientists across the MENA region into a remote talent community offering expert sessions, curated professional development, peer networking, and job-matching opportunities. Members engage in learning, leadership, and collaboration to accelerate careers and access top AI roles.

Build a production-ready web crawling and AI lead-qualification application: crawl and extract website content, analyze with LLMs to score/qualify industry-specific leads, produce structured outputs, and deliver a maintainable handover-ready product.

Lead the technical architecture and integration of enterprise-grade AI platforms (semantic search, RAG, generative/agentic systems), embed Responsible AI governance, manage risk/value trade-offs, enable zero-dependency handover through capability uplift, and design energy-efficient AI infrastructure across legacy and multi-cloud environments.

Design and build application-level AI features: implement RAG pipelines, prompt templates, retrieval strategies, and agentic workflows; integrate LLM-based functionality with legacy and multi-cloud systems; run structured evaluations, apply human-in-the-loop guardrails, and produce docs-as-code for handover to government engineers.

Hands-on Lead AI Engineer to design, build, and operate production-grade RAG, semantic search, embedding, and LLM orchestration systems in a UK government programme. Mentor engineers, implement Responsible AI guardrails, ensure security/observability, and enable capability transfer using Docs-as-Code and iterative delivery.