Top Machine Learning Jobs in Manchester

The Senior ML Data Engineer will enhance data workflows, collaborate with teams to build datasets, influence data strategies, and implement pipelines for effective data usage in AI/ML products.

Full-stack AI/ML Software Engineer to build HealthTech SaaS microservices, implement and integrate ML solutions, write high-quality code, author documentation, perform code reviews, and act as an SME on services and systems.

Build, train, evaluate and productionise custom ML and LLM models for customer feedback: fine-tuning pipelines, retrieval/reranking, summarisation, sentiment, evaluation frameworks, and monitoring. Collaborate with engineering, product and commercial teams, mentor colleagues, run experiments, and translate business needs into practical ML solutions.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

Lead and own ML platform end-to-end: data/feature pipelines, training and inference infrastructure, model registry, deployment, monitoring, and agentic AI stack. Design integrations across teams and third parties, ensure reproducibility, reliability, cost control, governance and audit trails, and grow a small engineering function supporting data scientists.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

As a Staff/Principal Machine Learning Engineer, you will optimize and scale multimodal inference systems, ensuring high performance and reliability in production environments.

Lead technical development and production deployment of advanced ML solutions (including LLMs, RAG, graph and sequence models) to improve customer operations. Provide hands-on engineering, mentor ML engineers, collaborate with product and backend teams, and drive MLOps and lifecycle strategy to route, disambiguate and resolve customer queries at scale.

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.

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.

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

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, 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.

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.

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.