Top Machine Learning Jobs in Manchester

Lead technical ML efforts to detect and prevent financial crime by designing, developing and shipping production deep learning, graph and sequence models. Provide IC technical leadership, mentor peers, work with product, engineering and MLOps to iterate models on a cloud-native platform, and measure production impact while minimising false positives and operational costs.

As a Machine Learning Engineer, you will develop production-ready ML solutions, collaborate with multidisciplinary teams, and contribute to Defence and National Security challenges.

As a Machine Learning Engineer, you will deploy AI/ML systems, translate client needs into solutions, and engage with users to provide support and improvements.

Join Starling as a Software Engineer to design, implement, and maintain ML-powered features, collaborating with engineers and data scientists, while delivering impactful solutions in a hybrid working environment.

Build and operate ML infrastructure for training, evaluation, deployment, inference, and experimentation. Improve reliability, scalability, latency, throughput, and cost efficiency. Create reproducible pipelines, observability, benchmarking, and platform tooling enabling researchers and engineers to ship models to production.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

Design and build end-to-end ML systems for fraud detection: develop and deploy models, create production-ready features and real-time data pipelines, integrate with backend services, and ensure monitoring, security, and observability.

Design, develop, deploy, and improve production-grade machine learning and computer vision models. Evaluate model performance, analyze data, support MLOps/CI-CD pipelines, resolve production issues, and mentor junior engineers while collaborating with product and engineering teams to deliver robust, scalable ML solutions.

Lead a small senior data engineering team owning the end-to-end data platform: streaming, warehousing, modelling, pipelines, ML lift, and operational excellence. Drive delivery, coach engineers, review technical designs, enforce data contracts and quality, manage costs (FinOps), and partner with Product and leadership to set roadmaps and risk. Build and grow an emerging ML function.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Lead technical authority for machine learning systems in the Defence domain. Define architectures, functional and non-functional requirements, solve cross-project technical challenges, guide strategy, mentor engineers, and deliver scalable AI solutions for high-stakes clients requiring UK security eligibility and regular on-site presence.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

As a Lead Machine Learning Engineer, you will set technical direction for ML projects, design scalable systems, mentor engineers, and drive innovation. You'll ensure successful project outcomes while balancing trade-offs and guiding team priorities.

Lead development of ClickHouse's Python connector and SDKs, build integrations with orchestration and transformation tools, drive AI/LLM integration strategy for production data workflows, engage with open-source community, and collaborate across product and platform teams to deliver enterprise-grade data integrations.

Design, build and deploy production-ready AI/ML solutions (including NLP, computer vision and generative AI) for UK public sector clients. Implement MLOps, develop scalable data pipelines and API-driven services, integrate Azure AI/LLM platforms, ensure responsible AI practices, and support proposals, PoCs and knowledge sharing across consulting teams.

Lead development and deployment of AI systems, design scalable ML software, mentor junior engineers, and collaborate with teams to solve client challenges.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.