Top AI Jobs in Manchester

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Lead modernization of month-end and year-end close processes using AI and automation. Prepare, review, and validate journal entries, accruals, and financial statements. Implement anomaly detection, automated reconciliations, variance analysis, and predictive insights. Collaborate with data teams to structure finance data for ML use cases and design audit-ready, scalable reporting workflows.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Analyze and classify technical content for security vulnerabilities, apply pattern recognition to improve AI model threat detection, design and evaluate security problems, and collaborate asynchronously with domain experts to produce high-quality outputs.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

Lead AI-enabled financial planning and strategic analysis, build data-backed business cases, refine unit economics, deliver executive-level insights, integrate ML into FP&A, and track KPIs to drive profitability and strategic decisions.

Manage and optimize end-to-end account reconciliations, intercompany eliminations, and chart-of-accounts governance. Identify discrepancies, perform variance analysis, and implement AI-driven automation and anomaly detection to reduce manual effort and accelerate close. Collaborate with cross-functional teams to resolve mismatches and improve financial data quality and reporting accuracy.

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

Provide private equity expertise to evaluate and create high-quality financial and investment content for training AI systems. Review financial models, market analyses, deal documents, support due diligence, deal sourcing insights, and give structured feedback to improve analytical accuracy.

Lead integration of AI-driven tools into tax provision, planning, and multi-jurisdictional compliance. Design ML/analytics solutions for sales and payroll tax, enhance regulatory filings, support audits, and collaborate with finance, legal, and technology teams. Monitor tax regulation changes, document AI tax models for transparency and governance, and continuously refine models for scalability, reliability, and compliance.

Design realistic civil litigation scenarios, draft attorney-level gold-standard responses, evaluate and grade AI-generated legal outputs using structured rubrics, provide detailed written feedback, and participate in onboarding and calibration. Minimum 20 hours/week; remote work across US, Canada, or UK.

The AI Creative Designer creates high-quality, AI-generated visuals for marketing campaigns, collaborating with teams to optimize visual content for conversion rates.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

The AI Operations Specialist will support CoinMarketCap's AI team by conducting feature evaluations, developing tools and automations, managing outreach, and collaborating with internal stakeholders to enhance AI operations.

The Solutions Specialist will engage with customers, define AI workforce visions using Microsoft 365 tools, drive adoption of AI solutions, and support strategic planning and delivery processes.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The Data & AI Portfolio Lead drives the development and integration of Fujitsu's Data & AI portfolio in the UK, aligning with strategic objectives and managing offerings throughout their lifecycle while providing leadership to product managers.

As an AI Product Manager at n8n, you'll develop AI-driven product experiences, coordinate with various teams, and innovate through user-centric design, focusing on AI trust and building.

As a Senior AI Engineer, you will develop AI-powered features, integrating LLM APIs to enhance user workflows while collaborating with teams to ensure reliability and scalability.

Test and validate Spanish (Mexican) voice AI agents, review recordings and transcripts, identify language/pronunciation and workflow issues, provide structured feedback, and support live customers via email/tickets during US Pacific Time business hours.

The role focuses on deploying AI SDR agents and optimizing sales processes through automation, enhancing productivity across the revenue team while requiring hands-on experience in AI implementation in B2B sales environments.

The Applied AI Engineer will develop and deploy AI features, enhance model performance, optimize systems for reliability, and collaborate with teams to address complex problems.

As a Technical Product Manager for AI Systems, you will define system requirements, collaborate with engineers, ensure product quality, and align AI capabilities with user needs.