Top Machine Learning Jobs in Manchester

Lead technical pre-sales engagements for enterprise email security customers. Partner with sales teams, conduct workshops and presentations, architect tailored solutions, and guide migrations from legacy Secure Email Gateways to Abnormal AI’s API-based platform. Build trusted customer relationships, troubleshoot migration challenges, provide product feedback, develop enablement content, and represent the company at industry events.

Provides customer-facing threat analysis and fraud prevention expertise for behavioral biometrics solutions. Responsibilities include advising financial institutions, analyzing fraud detection performance, deploying rules for attacks, supporting data science research into emerging threats, delivering reporting and insights, educating customers, leading workshops, and contributing to sales enablement and product strategy.

Leads complex customer audits, due diligence, and RFI/RFP engagements; oversees compliance response quality, customer communications, governance, process improvement, tooling, and team development. Partners with Sales, Legal, Information Security, and executives to address high-risk inquiries, maintain response documentation, improve workflows, and ensure accurate, customer-ready outputs.

Develop data-driven insights, predictive models, optimization solutions, and simulation-based decision-support tools for semiconductor manufacturing. Analyze manufacturing and operational datasets, apply statistical and machine-learning techniques, design experiments, and improve planning, scheduling, resource utilization, and factory performance. Collaborate with customers, domain experts, and engineering teams, communicate findings to technical and non-technical audiences, and contribute to manufacturing intelligence research and innovation.

Drive enterprise software sales through prospecting, product demonstrations, technical value communication, negotiation, closing, and customer expansion. Serve as the primary customer contact, maintain CRM and forecasting data, collaborate with product and engineering teams, gather customer feedback, and support adoption. The role focuses on Replit’s AI-powered developer platform and requires London-area availability with travel up to 25%.

Provides statistical leadership for Medical Affairs, real-world evidence, comparative effectiveness, HTA, and HEOR activities. Designs and analyzes observational, clinical, Phase IV, and indirect treatment comparison studies; evaluates data quality, bias, uncertainty, and applicability; supports evidence-generation strategies, reimbursement submissions, publications, and scientific communications. Collaborates with statistics, epidemiology, RWE, medical, and external scientific teams to translate complex analyses into actionable conclusions.

The Principal Solutions Architect leads technical solution design, partners with hyperscalers, ensures architectural integrity, and drives customer engagement through compelling narratives and demos.

Own and improve production machine learning pipelines focused on accuracy, efficiency, and trustworthiness. Build LLM evaluations, judges, datasets, metrics, and benchmarks; run experiments across prompts, models, and pipeline designs; and reduce LLM costs through smaller task-specific models. Expand anonymization capabilities, evaluate open-source models, and collaborate with quality engineers to ship reliable ML features. Document findings and communicate technical trade-offs clearly.

Supports technical sales for HPC and AI solutions by gathering customer requirements, designing architectures, preparing proposals, delivering demonstrations and proof-of-concepts, and validating solutions. Collaborates with sales teams, customers, partners, and technical specialists to position solutions, manage opportunities, contribute to pipeline growth, and support successful knowledge transfer. The role also involves tracking emerging technologies, participating in forecasts, documenting activities, and developing expertise in enterprise infrastructure and cloud technologies.

Designs and integrates machine learning capabilities into game editors, engine tools, and game systems. Owns complex technical features, improves development pipelines and workflows, identifies technical risks, and delivers scalable, reliable solutions. The role also includes reviewing designs, mentoring engineers, conducting code reviews, and collaborating across disciplines to advance AI-enabled game development.

Conduct empirical AI safety research with mentor guidance, owning projects from hypotheses and controlled experiments through analysis and technical writing. Build and debug evaluation harnesses, agent environments, datasets, monitoring methods, and post-training experiments. Investigate model failures, alignment, deception, misuse, multi-agent risks, and evaluation reliability. Produce reproducible code, experiment logs, research analyses, and papers for potential submission to leading machine learning conferences.

Leads the EMEA and LATAM Advanced Services architecture delivery team, overseeing complex customer and partner projects across pre-sales and delivery. Responsibilities include recruiting and developing architects, collaborating with Sales, Product Management, Engineering, and Customer Experience, presenting enterprise solutions, managing escalations, ensuring customer satisfaction, and shaping the services portfolio. The role requires strategic services expertise, strong leadership, data-platform knowledge, executive communication, and the ability to travel extensively across the region.

Independently assess medical device software lifecycle processes and technical documentation under EU MDR, UK MDR, IEC standards, and related cybersecurity guidance. Review SaMD and AI-enabled devices, raise and resolve technical findings with manufacturers, interpret regulatory requirements, and deliver consistent assessments using established workflows with minimal oversight.

Support UK insurance pricing through price modeling, implementation, strategy, monitoring, and development of new products. The role balances pricing accuracy, profitability, and price-comparison competitiveness while collaborating with data scientists, product, and underwriting teams. It also involves developing pricing capabilities using actuarial methods, predictive modeling, machine learning, and AI, while continuing actuarial education and monitoring regulatory changes.

Leads AML transaction-monitoring optimization, rule testing, threshold tuning, scenario design, and false-positive reduction. Drives FIU automation and workflow improvements, evaluates AI and LLM tools, supports alert triage and investigations, and partners with Product, Engineering, Operations, and vendors on compliance technology integrations. Helps scale monitoring frameworks across products, jurisdictions, and transaction volumes while maintaining regulatory alignment.

Leads biostatistical activities for Phase II–III clinical trials, from protocol design through reporting and regulatory submission support. Responsibilities include statistical analysis planning, sample size calculations, SAP development, TLF review, database lock support, safety reporting, regulatory responses, and oversight of programming or CRO work. Collaborates with cross-functional clinical teams and uses SAS or R for analyses, modeling, simulation, exploratory work, and quality control. Coordinates statistical activities across studies and applies advanced statistical and machine learning methods.

Drive partner-led CCaaS growth across EMEA and APAC by recruiting, onboarding, and scaling strategic partners. Lead co-selling motions, commercial opportunities, partner enablement, packaged offerings, forecasting, and performance reviews. Translate Zendesk AI and contact center capabilities into partner use cases and revenue opportunities while collaborating with Sales, Marketing, Product, Engineering, Solutions Consulting, and Customer Success teams.

Develop, debug, test, and optimize machine learning models, training pipelines, inference systems, numerical methods, and supporting infrastructure. Build reproducible Python workflows, diagnose computational issues, validate implementations, use coding agents, and document technical findings. This remote role requires approximately 15 hours per week and rapid task availability.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Serves as a customer-facing fraud and identity subject matter expert across pre-sales, onboarding, and expansion. Advises enterprise customers on risk profiles, fraud strategies, identity workflows, integrations, regulatory hurdles, and implementation best practices. Leads onboarding and go-live readiness, coordinates cross-functional teams, validates milestones, and helps customers optimize verification workflows, reduce friction, accelerate deployment, and maximize product value.

Lead a small team developing secure, reliable agentic AI capabilities. Responsibilities include setting technical direction, building agent monitoring, evaluation, and guardrail frameworks, performing machine learning tasks, translating research into production features, mentoring engineers, and contributing hands-on code and technical designs. The role focuses on agent collaboration, trust, security, quality measurement, and scalable software delivery.

Leads global AI-first MarTech engineering strategy, architecture, governance, compliance, and delivery. Oversees scalable digital platforms, public-facing properties, GenAI applications, R&D, proof-of-concepts, and automated compliance capabilities. Builds and mentors a global team of engineering and AI professionals, manages vendors, and partners with marketing, business, cloud, security, privacy, infrastructure, and legal stakeholders to deliver secure, high-performance digital experiences.

Leads end-to-end AI-powered insight and market research programmes for major client accounts. Responsibilities include shaping briefs, advising clients, managing scopes, budgets, timelines and resources, supporting pitches, leading consultants, and improving research delivery through AI-enabled tools. The role requires commercial research expertise, strong client leadership, organizational skills, and curiosity about emerging AI technologies.

Own the vision, strategy, roadmap, integration, commercialization, and executive stewardship of Kaltura’s new AI-powered learning and enablement platform. Lead 0-to-1 MVP delivery and post-MVP expansion across AI course generation, conversational tutoring, multimodal learning, simulations, and personalized journeys. Partner with engineering and GTM teams on architecture, pricing, packaging, positioning, enterprise sales, and integration of acquired products.

Analyzes fraud and financial crime performance for a virtual credit card, producing AML and fraud reporting, monitoring losses and alerts, optimizing rules and thresholds, and supporting regulatory and card-scheme compliance. The role conducts transaction analytics, validates new fraud solutions, investigates incidents, manages control enhancements, and partners with Product, IT, Operations, Compliance, and payment schemes to improve fraud controls and support safe product launch and ongoing performance.