Top Machine Learning Jobs in Manchester

Design and lead architecture for agentic AI, knowledge graph, semantic, and enterprise data platforms supporting supply chain systems. Build reusable data models, ingestion pipelines, integrations, entity resolution, schema alignment, validation, and graph capabilities. Evaluate emerging technologies, define scalable architecture and governance patterns, establish quality controls and evaluators for agentic systems, and mentor technical teams while influencing product and engineering direction.

Develop and deploy data science, machine learning, and AI solutions for secure government and intelligence environments. Responsibilities include predictive modelling, NLP, graph analytics, data integration, anomaly detection, model validation, dashboards, and production deployment. The role collaborates with engineering and operational teams to deliver automated insights and decision-support capabilities, while contributing to AI/ML strategy and technical roadmaps.

Executive leader responsible for globally scaling Customer Success across delivery, support, engineering, education, and project management. The role focuses on reducing churn, increasing adoption and expansion, optimizing the customer lifecycle, proving customer value, incorporating customer feedback, improving operational efficiency, and building talent. The VP partners closely with Sales, Product, Marketing, Finance, and Legal while serving on the executive leadership team and reporting to the CEO.

Own the end-to-end delivery of applied machine learning products, from framing customer problems and building data pipelines to deploying, monitoring, and measuring model impact. Develop models for operational data using Python, SQL, dbt, Snowflake, and AWS; define evaluation and drift monitoring; conduct A/B tests or causal analyses; and partner with product and engineering teams to embed ML into customer workflows.

Develop and maintain Elasticsearch’s Inference API and plugin framework, integrating internal and external AI providers. Responsibilities include API and protocol design, streaming, asynchronous execution, rate limiting, configuration, billing integration, error handling, open-source contribution reviews, incident response, and comprehensive unit, REST, and rolling-upgrade testing. The role requires advanced Java expertise, concurrency and parallelism knowledge, API design skills, cross-functional collaboration, and autonomous work in a distributed team.

Own Quince’s international forecasting and replenishment architecture, combining classical forecasting, machine learning, and AI agents. Build prototypes and analytical tools in Python, SQL, and Streamlit; partner with data and engineering teams to productionize successful solutions. Improve forecast accuracy, reduce stockouts, automate planning workflows, support new-market launches, and translate between planners, engineers, and leadership. Establish trusted human-machine decision processes and continuously improve planning systems across international markets.

Leads complex Defence and national security programmes spanning AI strategy, R&D, digital product development, and deployment. Oversees portfolios, develops growth proposals, mentors teams, manages senior military and civilian relationships, and advises clients on AI implementation and operational outcomes. Requires substantial Defence experience, transformation programme leadership, digital product delivery, commercial consulting expertise, and UK Security Clearance eligibility. The role involves working onsite with UK customers two to four days weekly and travelling throughout the UK when required.

Leads Tide’s global KYX engineering organization across onboarding, continuous due diligence, identity, risk scoring, data science, and ML. Owns engineering strategy, organization design, model lifecycle, regulated AI deployment, and measurable improvements in conversion, due diligence quality, automation, and servicing costs. Partners with operations, policy, risk, compliance, product, and IAM teams across multiple markets while building globally reusable platforms with market-specific logic isolated.

Drive adoption of Rapsodo Golf solutions across UK golf ranges, clubs, and facilities. Responsibilities include prospecting, relationship building, on-site demonstrations, full-cycle sales, contract negotiation, installation coordination, post-installation support, CRM pipeline management, territory planning, event representation, and sharing customer and competitor insights with internal teams.

Leads project controls and performance consulting engagements for complex capital projects and programmes. Assesses client environments, develops recommendations, facilitates workshops, deploys tailored methodologies and digital solutions, and supports PMO and controls functions. The role also contributes to bids, business development, marketing initiatives, internal product development, and team leadership while managing client relationships and delivering reports to senior stakeholders.

The Director of FP&A will own budgeting, rolling forecasts, integrated financial modeling, cash flow and headcount planning, SaaS KPI reporting, variance analysis, board reporting, and PE sponsor reporting. The role will improve planning infrastructure across NetSuite, Salesforce, Pigment, and Bob, apply AI to finance workflows, and lead and develop the FP&A team across a multi-entity, multi-currency SaaS business.

Build scalable, low-latency backend APIs, event-driven services, integration layers, and microservices supporting personalization and recommendation experiences. Partner with AI/ML and data engineers to deploy models, expose AI services, and develop React applications. Improve security, observability, reliability, performance, scalability, and operational efficiency while using AI-assisted engineering tools to enhance delivery and code quality.

Manage the full sales cycle across EMEA, including prospecting, pipeline generation, client meetings, contract negotiation, and closing. Build strategic partnerships with mobile gaming and other app-focused clients, exceed revenue quotas, and collaborate with Customer Success, Marketing, and Product. Represent the company at industry events, track mobile advertising trends, and use AI technologies to improve prospecting and sales performance.

Own production data and feature pipelines supporting machine learning systems, including training data preparation, feature engineering, model deployment, versioning, retraining, monitoring, and CI/CD. Build batch and ELT pipelines using Python, PySpark, and cloud data platforms. Troubleshoot live systems, make architecture decisions, partner with clients and data scientists, and mentor engineers while delivering solutions with substantial autonomy.

Build BLP’s core software across infrastructure, backend, machine learning, and product extension platforms. Responsibilities include operating secure and observable cloud infrastructure, developing performant distributed systems, applying AI to business problems, and enabling customer process automation. The role emphasizes formal reasoning, correctness by construction, maintainable systems, type systems, and functional programming. Work is available onsite in Zurich or remotely within Europe.

Build and deploy production-grade AI solutions, including LLM agents, multi-agent workflows, RAG systems, classical ML, and speech models. Develop reliable, secure, observable, and scalable AI platforms using strong software engineering and MLOps practices. Own solutions from client scoping through monitoring and continuous improvement, collaborate with technical and business stakeholders, mentor engineers, and drive innovation in enterprise AI.

Participate in a 24-month rotational engineering analyst program focused on data science. Apply data analysis, profiling, feature engineering, statistical methods, and machine learning to solve business and engineering problems. Build scalable analytical processes, models, and tools using Python, JavaScript, Java, CSS, and related technologies. Collaborate with engineering and business teams to translate data insights into practical recommendations and improve decision-making.

Design and develop scalable AI-powered solutions for complex enterprise data and analytics problems. Translate ambiguous business needs into algorithmic approaches, build AI architectures and model pipelines, integrate capabilities into enterprise platforms, evaluate emerging AI methodologies, and document solution designs. The role requires strong machine learning, statistical, mathematical, software development, systems architecture, and communication skills.

Design and build scalable AI-powered solutions for complex enterprise data and analytics problems. Translate ambiguous business needs into algorithmic approaches, develop model pipelines and data-processing architectures, integrate AI capabilities into enterprise platforms, evaluate emerging AI methodologies, and document solution designs. The role requires strong software development, machine learning, statistical, analytical, mathematical, and communication skills.

Lead regional field sales teams, develop sales strategies and account plans, manage pipeline and forecasts, recruit and coach sales managers, close enterprise technology deals, and grow business through customers, resellers, and partners. The role requires strong technical knowledge of cybersecurity, cloud, networking, and IT infrastructure solutions, executive-level selling skills, and the ability to manage remote teams across the NEMEA region.

Leads the mid-market business development function, including team building, territory strategy, prospecting, negotiation, closing, pipeline management, and account acquisition and retention across pharma and biotech. Partners with marketing, strategy, and commercial operations on go-to-market execution. Represents the company at industry events and develops relationships with clinical trial sponsors while selling complex AI-powered SaaS solutions.

Leads a 25+ person organization of data scientists, machine learning engineers, and analytics engineers across Identity and Financial Crime. Owns data quality, governance, lineage, observability, fraud and financial-crime models, production performance, monitoring, retraining, and domain data products. Partners with engineering, product, risk, compliance, legal, and central data teams; influences upstream teams, develops managers and senior ICs, handles incidents, and scales hiring and technical strategy.

Build and deploy production machine learning systems for classification, retrieval, ranking, personalization, and evaluation. Develop training and inference pipelines, improve model quality and efficiency, create evaluation datasets and metrics, monitor production performance, debug issues, and ship reliable ML-powered features. The role emphasizes balancing accuracy, relevance, latency, cost, privacy, and reliability while collaborating with engineering and product teams.

Develop statistical and machine learning models using soccer tracking and event data to support player recruitment decisions. Build spatio-temporal models, metrics, analyses, and interpretation tools; validate models; communicate findings to professional club clients; and partner with engineering on cloud deployment and production reliability. The role also includes code review, model maintenance, and advancing analytical methods.

Design, build, deploy, and optimize scalable AI and machine learning systems using large datasets. Develop predictive models, recommendation systems, personalization engines, forecasting solutions, generative AI applications, and production ML pipelines. Collaborate with data, backend, and product teams to integrate models into applications, while monitoring performance, data quality, drift, reliability, and cost. Establish best practices for evaluation, experimentation, reproducibility, and deployment, and research emerging AI technologies.