Top Machine Learning Jobs in Manchester

The Product Marketing Director will drive global growth and reputation through market insights, effective messaging, product launches, and sales enablement in the cybersecurity space.

Lead the development and optimization of machine learning algorithms, owning the end-to-end model development and collaborating with Data Engineers for integration into live systems.

The role involves designing scalable data pipelines, implementing custom ML algorithms, and working on microservice architectures for ad optimization models.

Lead ML strategy and delivery for Workforce Management: forecasting, routing, assignment, escalation and time-to-completion prediction. Build, ship and maintain production ML systems, coach and grow a team of ML scientists, work cross-functionally to turn operational problems into pragmatic ML solutions, and improve customer and operational outcomes.

Design and implement large-scale AI/ML systems using LLMs and RAG. Develop data pipelines, optimize models, and collaborate with teams on actionable intelligence solutions.

The Senior Applied ML Engineer will build and maintain production ML systems for catalogue decision-making, improving data quality, product categorization, and discoverability.

The Machine Learning Engineer III will design and optimize AI systems, utilizing techniques like deep learning and statistical modeling to solve real-world business problems, collaborate globally, and communicate complex data effectively.

Design, build, and deploy end-to-end ML and generative AI solutions (ranking, recommender, chatbots, agentic systems). Handle data engineering, feature engineering, modeling, evaluation, deployment, monitoring, and cross-functional communication to deliver business impact.

Lead development of enterprise commercial intelligence: build data models (pipeline, forecasting, segmentation), deploy AI/ML for forecasting and churn, create dashboards, establish data governance, partner with senior leaders to drive insight-led decisions and adoption across global teams.

As a Machine Learning Engineer Intern, you will develop AI models, work with deep learning algorithms, and enhance understanding of neural mechanisms in the Brain & AI team at Tether.

Develop and evaluate AI/ML and Generative AI/LLM models from POC to production, perform data science and statistical analyses to support business decisions, document and assess model risk, publish patents/papers, collaborate with SMEs, and provide technical leadership while deploying solutions with modern Agile/DevOps and cloud practices.

As a Senior Machine Learning Engineer, you will build an ML platform, apply data analysis, and enhance ad technologies, collaborating with cross-functional teams to optimize ad experiences.

The Research Manager will lead AI-powered insight projects, manage client relationships, oversee team execution, and innovate using AI tools to improve insights delivery.

Deliver end-to-end data science projects: build and deploy ML/NLP and generative-AI solutions, design scalable data pipelines, integrate cloud services and APIs, implement RAG/vector-search applications, and collaborate with cross-functional teams to produce reusable tools and client-facing products.

Convert R&D prototypes into production-ready AI features. Build and operate real-time personalization, recommendation, search and ranking systems with low latency. Deliver cloud-native services on AWS with CI/CD, infrastructure-as-code, observability, and testing. Collaborate with researchers, product, and engineering to measure and improve model performance.

Lead AI Engineer to create and productionise AI/ML solutions (personalisation, recommendations, search, LLMs). Lead an AI Engineering function, define technical direction, mentor engineers, drive engineering best practices, and deliver cloud-native, scalable, low-latency services on AWS.

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.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

The Forward Deployed Software Engineer will customize AI solutions for enterprise customers, maintain technical ownership, and bridge between support and engineering.

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

Lead and grow a team of ML scientists to build and productionise credit underwriting, pricing, limits, and lifecycle models. Define Borrowing's ML roadmap for UK growth, new segments, and EU expansion, improve feature engineering and data use, and raise standards for model quality, governance, and iteration speed.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

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.

Build and operate production-grade Kubernetes clusters and CI/CD (Harness/GitOps) for ML lifecycle. Deploy and optimise GPU-backed inference (CUDA, TensorRT, Triton, TorchServe), implement observability (Prometheus, Grafana, Dynatrace), manage model registry/MLflow, enforce auditability and reproducibility, enable progressive delivery and continuous training/monitoring, and run on‑call reliability processes with alerting and runbooks.