Top Machine Learning Jobs in Manchester

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

Transform operational data into actionable insights by building semantic models, reporting solutions and metrics (Power BI/Fabric, DAX, M, SQL). Ensure data quality, governance, access controls, troubleshooting, documentation, and stakeholder collaboration to enable self-service analytics.

Lead Vegetation Intelligence product, owning roadmap from ML detection models to customer-facing risk products. Advance detection models, integrate outputs into outage and ignition risk, run user research, and translate model capability into actionable B2B products used in the field.

Own and grow the EMEA territory by building pipeline, managing full sales cycles, closing enterprise travel-tech deals, and developing partnerships with TMCs and travel providers. Represent the company at events, engage senior executives, and share market feedback with Product and Leadership to drive strategic outcomes.

Own and translate complex business problems into technical product backlogs and user stories. Drive AI-enabled, cloud-based features (LLMs, ML), collaborate with engineering and stakeholders, manage priorities, triage issues, measure product performance, and ensure scalable, secure integrations via APIs and webhooks.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Lead platform product ownership bridging cloud and firmware strategy and execution. Manage and prioritize backlog, engage customers, collaborate with R&D, define releases, and drive agile delivery aligned with product leadership.

Own the Device Intelligence product roadmap for tier‑1 network service providers. Define PRDs, AI/LLM-assisted workflows, and technical requirements; lead discovery, backlog prioritization, and cross-functional delivery; engage strategic customers and support sales with competitive positioning.

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

Lead AI product strategy and execution for EMEA, building and delivering a portfolio of enterprise AI products that drive measurable business value. Engage executives, shape roadmaps, partner with cross-functional teams, ensure governance and regulatory compliance, and mentor stakeholders to accelerate scaled production deployments and adoption.

Lead and deliver statistical support for Phase II-III clinical trials embedded with a sponsor: design input, SAP/sample size, interim/final analyses, oversight of programmers/statisticians, regulatory submissions, and collaborate cross-functionally to ensure compliant, high-quality statistical deliverables. Apply advanced statistical methods and ML/DL for analytics and process automation.

The role involves embedding in various parts of the business to identify and solve AI problems, producing working solutions through short sprints, and evaluating their effectiveness while facilitating adoption.

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.

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.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.

The Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

The Customer Value Architect will engage with customers to ensure the effective adoption and value realization of the Neara platform, focusing on ROI metrics and customer relationships.

The Customer Success Manager will onboard and support Portuguese utility accounts, ensuring effective use of digital twin technology and driving long-term partnerships and customer satisfaction.

The Executive Partner manages a portfolio of clients, providing expert guidance in Data & Analytics, mentoring executives, and ensuring client value through various engagements. Responsible for retention and growth, the role emphasizes collaboration with internal teams and requires strong executive presence.

The role involves designing, building, and deploying ML systems, supporting stakeholders, and operationalizing AI applications in Defence.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.