Top Machine Learning Jobs in Manchester

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.

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.

Leads technical direction for GitLab’s Core DevOps services, covering CI, CD, planning, and source control. Defines architecture, quality metrics, migration strategies, and technical roadmaps; addresses systemic risk and complex design decisions; prototypes and writes code when needed; partners with Infrastructure, Security, SRE, and Product; adopts AI capabilities; mentors senior engineers; supports incident response and senior technical hiring.

Supports enterprise sales by discovering customer requirements, mapping them to SailPoint solutions, and delivering foundational implementations and proof-of-value engagements. Acts as a technical lead and consultative advisor, educating customers on architecture and best practices. Collaborates with sales, product, professional services, partners, and customer success teams while developing AI-driven and agentic solutions for demonstrations and customer outcomes.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

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 GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Provide expert technical advice on age assurance and digital identity technologies within online safety regulation. Lead research and evaluations, assess technical feasibility and risks, translate complex concepts for policy and leadership audiences, prepare briefings and demonstrations, monitor emerging trends, and engage with academia, industry, public bodies, and external technical groups.

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.

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.

Leads the technical vision, roadmap, governance, and delivery of Bupa’s Care Services data product portfolio. Partners with product managers and multidisciplinary squads to develop scalable, secure, reusable data and AI products. Establishes data architecture, modelling, analytics, quality, and governance standards across Azure, Snowflake, Power BI, and GCP. Provides technical leadership across multiple teams, manages dependencies, and identifies opportunities to apply AI, machine learning, automation, and advanced analytics.

Leads strategic R&D engagements from presales through delivery, translating scientific and business challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Builds trusted relationships with R&D executives, scientists, engineers, and technical teams; assesses data, compute, feasibility, value, staffing, and delivery plans. Develops reusable architectures and playbooks, oversees technical workstreams, evaluates emerging AI capabilities, and provides feedback to shape Microsoft Discovery products and scalable industry solutions.

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.

Manage NVIDIA’s relationships with cloud and technology partners, driving adoption of AI platforms and solutions. Develop partner strategies, quantify market opportunities, create value propositions, coordinate technical, business, and marketing resources, and cultivate customer references and emerging use cases. Lead ecosystem engagement across solution providers, integrators, startups, and enterprises, while supporting demand generation, community marketing, business development, and industry events.

Leads biomedical data science for clinical and health research, integrating clinical, observational, EHR, genetic, wearable, electrophysiological, and video data. Develops signal-processing methods, machine-learning models, probabilistic and time-series analyses, scalable data pipelines, and reproducible workflows. Validates clinically relevant models, supports disease phenotyping and predictive modeling, ensures compliance with pharmaceutical and healthcare standards, and communicates technical findings to clients and stakeholders.

Drive responsible AI adoption across the organisation by identifying automation opportunities, facilitating process-mapping workshops, training colleagues, developing guidance, and prototyping AI-powered solutions. The role builds an AI champions network, manages an opportunity pipeline, establishes governance guardrails, and collaborates with the Data, Systems & GIS team to implement internal tools. It is fully remote with travel for workshops and in-person collaboration.

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.

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.

Conduct computational analyses of genomic, transcriptomic, proteomic, and other biomedical datasets to identify drug targets, biomarkers, and disease subtypes. Apply machine learning, deep learning, and omics methods; integrate multi-omics data; review literature; interpret results; design validation strategies; and develop visualizations and reports. Collaborate with AI, biology, chemistry, imaging, and medical experts while contributing to agentic AI systems and internal research methodologies.

The Senior Data Scientist transforms ambiguous business questions into actionable insights using Python, SQL, statistical methods, forecasting, regression, classification, segmentation, and machine learning. The role involves analyzing complex datasets, validating models, engaging stakeholders, communicating findings to senior audiences, and translating analysis into commercial decisions. Desirable experience includes time-series modeling, churn and propensity models, cloud data platforms, Streamlit, Power BI, and financial services.

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.

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.