Top Machine Learning Jobs in Manchester

Develop machine learning and statistical models, analyze large datasets, conduct exploratory analysis and controlled experiments, and deliver actionable insights for sports and gaming products. The role partners with Fraud, Responsible Gambling, Trading, Branding, and other stakeholders to solve business problems, maintain scalable data science infrastructure, communicate findings, and promote innovative data science practices.

Lead development of probabilistic, real-time betting models for in-play sports markets. Design, develop, validate, and deploy scalable, computationally efficient predictive models using Python/R and modern ML frameworks. Collaborate with trading, software and architecture teams, mentor junior data scientists, research novel approaches, and ensure models meet business objectives and production requirements in a fast-paced environment.

Perform malware and threat research across the attack lifecycle, validate and improve Falcon detections, collaborate with engineering and ML teams, automate analysis, support external security testing, and translate findings into product protections.

Lead and grow a distributed engineering organization building customer-facing security capabilities: proprietary scanners, AI/ML detection engines, agentic remediation, vulnerability management, and security foundations. Set vision and roadmap, drive architecture and delivery, partner with product management, establish engineering standards, and represent the group in cross-functional and customer forums.

Design and develop cloud-based data platform solutions, including data pipelines, ingestion, transformation, cleansing, integrations, and data applications. Translate technical requirements into detailed designs, write reliable code, develop test automation, troubleshoot operational issues, tune batch and real-time processing, secure cloud data platforms, and implement CI/CD and monitoring. The role also involves advising client developers and defining efficient operational processes.

Designs, governs, and delivers enterprise Workday solutions across Build, Extend, Prism, and Orchestrations. Translates business needs into secure, scalable applications and integrations; establishes development, data, security, testing, and change-management standards; leads complex initiatives; manages stakeholders; and mentors Workday developers and analysts. The role requires expertise in Workday data models, security, business processes, reporting, REST APIs, and integration patterns.

Leads strategic AI and machine learning initiatives from concept through production. Designs scalable solutions connecting data, models, platforms, and systems; develops reusable engineering patterns; improves solution quality and reliability; conducts analysis supporting strategic decisions; builds stakeholder partnerships; and provides organizational leadership, mentoring, and innovation across the enterprise.

Leads non-financial risk insight development for Commercial & Institutional banking. Builds dynamic dashboards and self-service risk intelligence using analytics, AI, machine learning, automation, and visualization tools. Translates complex risk data into actionable narratives, supports risk-based decisions, embeds risk frameworks, influences senior leaders, and collaborates across the three lines of defence. Also leads a team and trains business users to apply data-driven risk insights.

Join Arcadis’s two-year graduate programme as a Data Scientist, contributing to client projects involving descriptive and predictive modeling, machine learning, and mathematical optimization. You will support analytics solutions across water, energy, cities, transport, and buildings, particularly asset investment planning. The role includes stakeholder consultation, client engagement, professional development, and collaboration with multidisciplinary teams.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

Build AI and automation solutions using Microsoft Fabric, Power Platform, LLMs, intelligent document processing, agentic AI, and Power BI. Lead responsible AI practices, stakeholder discovery, training, adoption, and MVP delivery across capital project consulting. Maintain billable involvement in Technical Due Diligence engagements, identify client-facing AI opportunities, and support proposals and commercial delivery. The role requires Python, SQL, data pipeline development, governance awareness, strong communication, and UK work authorization.

Lead technical strategy and architecture for personalization, search, and recommendation systems. Deliver scalable ML-powered features, mentor senior engineers, and improve engineering quality across cross-functional teams.

As a Principal Engineer at M&S, you'll drive technical strategy, influence architecture, and mentor engineers while delivering on personalization, search, and machine learning features in collaboration with cross-functional teams.

Designs and develops scalable AI-powered solutions for enterprise data and analytics problems. Translates ambiguous business needs into algorithmic approaches, builds model pipelines and decision systems, integrates AI capabilities into enterprise platforms, evaluates emerging methodologies, and documents solution architectures. Requires strong software development, machine learning, statistical, mathematical, system design, communication, and large-dataset skills.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Drive end-to-end B2B sales of Data and AI consulting services in the US market. Responsibilities include prospecting, pipeline generation, solution selling, account planning, business-case development, executive stakeholder engagement, partner collaboration, and closing enterprise and mid-market opportunities involving Databricks, Lakehouse modernization, data engineering, analytics, AI/ML, and GenAI.

Supports the design, development, and deployment of applied AI systems under senior engineer guidance. Contributes to AI feature development, follows engineering standards, participates in code reviews and technical discussions, and builds expertise across modern AI and cloud technologies. The role emphasizes learning, collaboration, and progression toward more senior engineering responsibilities.

Leads a global team of Defence and Intelligence pre-sales solution architects. Develops technical sales strategies, designs geospatial and Earth Observation solutions for military and ISR workflows, leads customer demonstrations and pilots, supports complex government procurements, and partners with sales, product, engineering, professional services, and defense organizations. Requires deep defense intelligence expertise, geospatial architecture knowledge, leadership experience, and active or obtainable security clearance.

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.

Provides executive accountability for a $100M+ Cisco CX Services portfolio serving a strategic enterprise customer. Leads delivery governance, C-suite advisory, commercial and P&L oversight, AI-enabled program intelligence, network and infrastructure transformation, vendor orchestration, and large multidisciplinary teams. Oversees complex Cisco Nexus, ACI, Catalyst Center, Software-Defined Access, data center, and campus initiatives while ensuring contractual compliance, risk management, operational excellence, and revenue growth.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, RAG, hybrid search, and agentic workflows. Analyze large-scale intellectual property datasets, design experiments, evaluate and benchmark models, define reasoning strategies, and translate findings into product recommendations. Collaborate with product managers, IP experts, and engineers to deliver scalable, customer-facing solutions.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, generative AI, retrieval, and hybrid search. Define multi-step reasoning workflows, analyze large-scale intellectual property datasets, establish model evaluation and benchmarking practices, and translate experiments into product recommendations. Collaborate with product teams, intellectual property experts, and engineers to deliver scalable, customer-facing solutions.

Leads the identification, development, integration, and global deployment of AI and automation solutions for legal editorial, metadata, and content operations. The role supports AI strategy, evaluates designs against governance and quality standards, manages cross-functional projects, reports data-driven outcomes, tracks industry trends, documents improvements, and promotes responsible AI use.

Own technical and strategic hiring across AI, machine learning, infrastructure, software engineering, product, and leadership roles in the UK. Build long-term relationships across the AI and technology ecosystem, engage passive candidates, attend industry events, and partner directly with founders and senior leaders. The role requires credible technical conversations, autonomous decision-making, strong ownership, and occasional support for broader People topics.

Leads the architecture and delivery of complex Azure, Microsoft 365, cloud, and AI solutions for strategic customers. Translates business needs into secure, scalable architectures; manages requirements, design governance, technical quality, deployment, and stakeholder alignment. Acts as a trusted technical advisor, drives presales and delivery outcomes, develops reusable intellectual property, mentors architects, and promotes Microsoft technologies through thought leadership and customer engagement.