Top Machine Learning Jobs in Manchester

Develop machine learning and statistical models, analyze large datasets, conduct exploratory analysis and A/B tests, and translate findings into actionable business insights. The role partners with Fraud, Responsible Gambling, Trading, and Branding stakeholders, contributes to scalable data science infrastructure, communicates results through visualizations and presentations, and promotes innovative data science methods across the analytics team.

Drive sales of CDW’s Data and AI solutions across data modernization, governance, analytics, cloud platforms, and applied AI. Own sales cycles from qualification through close, build pipeline, develop proposals and business cases, engage executive stakeholders, and collaborate with account teams, solution architects, Microsoft, and other partners. Lead customer conversations about data readiness for AI, position assessments and transformation programs, support bids, forecast accurately, and achieve revenue and gross-profit targets.

Manage and expand strategic partner alliances for SailPoint’s enterprise software business. Develop joint business, marketing, technical certification, and go-to-market plans; generate partner-sourced pipeline; coordinate account mapping, co-selling, enablement, promotions, and implementation capacity. Serve as the primary liaison between SailPoint and partner organizations, monitor performance and KPIs, ensure compliance and delivery quality, and present quarterly business assessments. The role requires extensive enterprise partner-management experience, analytical skills, executive communication, and approximately 50% travel.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Manage a team of machine learning engineers developing credit and lending models for international markets. Set technical strategy, guide advanced ML solutions, partner with product, engineering, analytics, design, and risk teams, and ensure scalable underwriting capabilities. Provide hands-on technical leadership, clarify complex problems, manage trade-offs, and mentor engineers while contributing to Affirm’s long-term machine learning strategy.

Lead AI engineering innovation across conversational analytics and emerging analytical AI products. Develop governed, testable, scalable solutions using Python, SQL, APIs, cloud technologies, and automated workflows. Prototype and evaluate analytical agents, anomaly detection, process intelligence, and intelligent workflows. Establish engineering standards, evaluation frameworks, testing approaches, documentation, and reusable assets while partnering with product, data, governance, security, privacy, risk, and architecture teams to move successful concepts into production.

Develop and evaluate machine learning models for recommendations, personalization, customer modeling, and predictive analytics. Explore data, engineer features, conduct experiments and A/B tests, and communicate results and trade-offs. Collaborate with Product, Engineering, MLOps, Commercial, and Marketing to productionize models, monitor performance, and improve data quality. Write tested, maintainable Python and SQL using reproducible software-development practices, while responsibly applying AI-assisted tools.

Leads digital delivery and optimisation across AECOM’s England and Wales water operations. Develops digital strategies, advises clients on transformation, governance, platforms, and roadmaps, and identifies opportunities for AI, data science, automation, and innovation. Coordinates delivery teams, supports capability development, contributes to bids and tenders, and facilitates client workshops and stakeholder presentations. The role combines technical leadership, strategic consulting, client engagement, and programme-level digital implementation.

Lead the design and delivery of modern data and AI solutions for multiple customers. Provide architectural direction, technical assurance, and thought leadership while advising senior stakeholders on strategic and technical decisions. Manage and mentor architects and engineers, develop standards and account strategies, support agile teams, build customer relationships, and guide scalable, distributed, cloud-based applications. The role also involves business development, technology advocacy, and fostering inclusive, high-performing teams.

Own the strategy, roadmap, development lifecycle, and go-to-market activities for fraud analytics products. Lead customer discovery, prioritize product improvements, analyze complex data, collaborate with development and data science teams, and use market and customer insights to improve user outcomes. The role requires fraud prevention expertise, statistical modeling and AI/machine learning knowledge, strong stakeholder communication, and flexible UK-US working hours.

Drives full-cycle sales of Data and AI solutions, including data readiness assessments, modern data platforms, governance, analytics, applied AI, and managed services. Builds pipeline, leads customer discovery, develops proposals and business cases, negotiates deals, and achieves revenue targets. Partners with account teams, Microsoft, and other vendors to deliver transformation opportunities. Advises senior technology stakeholders on data readiness, regulatory considerations, AI adoption, and multi-year commercial roadmaps.

Leads CDW’s UK Data & AI Solution Sales practice, defining strategy, propositions, go-to-market plans, and profitable growth. Builds data-readiness and AI-adoption offerings, manages senior vendor and customer relationships, drives revenue and partner programs, and ensures responsible, compliant delivery. Develops teams, certifications, forecasting, staffing, operational standards, and cross-functional collaboration across sales, security, cloud, delivery, marketing, legal, and compliance.

Lead international product design for Clio’s legal SaaS platform, beginning with France. Own end-to-end design from discovery through launch, develop scalable localization patterns, improve design systems, conduct customer research, and create polished, accessible AI-powered experiences. Partner with Product and Engineering, influence cross-functional decisions, mentor through critique, and establish repeatable design practices for new markets.

Serve as a technical advisor to ISPs throughout discovery, demonstrations, proof-of-concepts, integration, deployment, and support. Integrate Plume solutions with customer BSS/OSS, CRM, ticketing, and AI platforms. Partner with sales to drive revenue, deliver presentations and QBRs, support trials, provide product feedback, and stay current on networking, cloud, and AI technologies. The role is remote within the UK or Netherlands and requires travel exceeding 70%.

Lead and build a new platform engineering team responsible for cloud-agnostic deployments across AWS, other clouds, private cloud, and on-premises environments. Own Kubernetes infrastructure, Terraform, GitOps, CI/CD, observability, reliability, compliance automation, FinOps, and AI/ML infrastructure. Hire and develop engineers, establish operating standards, support SOC 2, ISO 27001, and GDPR controls, and deliver portable, secure, auditable platform foundations for data catalog, knowledge graph, and integration services.

Own and build Oversee’s product marketing function, including ICP definition, positioning, persona messaging, competitive and win/loss research, product content, sales enablement, and end-to-end product launches. Partner closely with product, sales, growth marketing, and executives to translate technical AI and travel technology capabilities into compelling commercial messaging, establish repeatable GTM processes, and measure launch performance.

Designs challenging competitive data science and machine learning tasks, reproducible execution environments, reference solutions, automated tests, and evaluation criteria. Uses Python, statistical modeling, mathematical reasoning, and debugging to assess AI coding agents, identify data leakage and implementation flaws, validate solution correctness, and document methodologies. Requires a verifiable Kaggle Expert-level profile, strong practical programming skills, and the ability to independently test and explain technical solutions.

Own and develop production machine learning components for a dynamic pricing system. Build probabilistic models, experimentation and measurement systems, monitoring, alerting, guardrails, staged releases, and replayable pricing decisions. Investigate commercial pricing adjustments, improve business metrics, and collaborate with engineering, product, platform, sales, and commercial teams. The role requires hands-on production coding, operational accountability, and safe deployment of automated decisions involving money.

Build and scale the ML platform supporting production forecasting, pricing, prediction, and optimization models. Responsibilities include deployment infrastructure, model inference and training, observability, monitoring for drift and degradation, data validation, evaluation and backtesting tooling, production data systems, and reliability ownership. The role also contributes to model improvements, time-series forecasting, and potentially probabilistic modeling and quantitative trading or energy optimization applications.

Annotate and label text, objects, and visual data for AI and machine learning projects. Review datasets for accuracy, follow detailed project standards, and maintain data quality. The role includes full onboarding and training, requires attention to detail and analytical reasoning, and can be performed remotely on a flexible full-time or part-time schedule.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Develop and deliver machine learning and analytics solutions using predictive modeling, computer vision, and generative AI. Improve Verisk products and processes while ensuring accuracy, interpretability, and timely delivery. Stay current with analytic innovations, mentor analytic interns, and share methodologies across the analytics community. Work with large, complex datasets across insurance, energy, financial services, and other industries.

Lead strategic relationships with Capital Markets organizations across EMEA, driving adoption of NVIDIA AI and accelerated computing solutions. Serve as the primary client contact, grow revenue and platform usage, develop account strategies, forecast business, and engage senior technology leaders. Collaborate with solution architects, business development, developer relations, cloud partners, hardware providers, and software developers. Communicate solution value, provide thought leadership, and travel to meet clients and partners.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Software engineering intern supporting the Platform Engines group and Policy Engine for SailPoint’s cloud identity security platform. Responsibilities include developing software, procedures, and test solutions; collaborating with software and QA engineers, technical writers, and product managers; and working in Agile teams. The intern will gain exposure to cloud and software technologies including Golang, Angular, AWS, Docker, Kafka, Kubernetes, REST, SQL, and Temporal.