Top Machine Learning Jobs in Manchester

The Principal Product Manager will lead product and commercial strategy in a complex domain, focusing on user-centric solutions and driving transformative change while collaborating across teams.

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

The Lead Data Scientist will set technical directions, oversee complex projects, mentor teams, and build relationships with clients while ensuring high-quality deliverables.

The role involves designing and testing AI solutions, managing research projects, collaborating with teams, and introducing new ML concepts for product development.

As a Staff Machine Learning Engineer, you will lead the development of complex ML systems and MLOps pipelines, mentor junior engineers, and ensure scalable and reliable solutions for retail workflows.

The Pricing Advisory professional will assist clients in enhancing pricing strategies through consultation, model development, implementation support, and training sessions, while managing stakeholder relationships and navigating challenges in pricing sophistication.

AI Trainers will complete tasks involving analyzing, editing, and annotating data to improve AI models with real ML expertise, including performance evaluation and providing technical feedback.

The role involves training and evaluating AI models, conducting AI training tasks, and providing expert feedback on their performance using machine learning skills.

The Senior AI/ML Developer will deliver AI features, integrate ML models, and oversee the full project lifecycle from concept through production deployment.

Build MCP servers and agentic workflows that securely connect LLMs to enterprise systems (Salesforce, Snowflake, Google Workspace), deliver production AI integrations, collaborate with stakeholders, document patterns, and grow the AI Enablement function.

As a Customer Experience Specialist, you'll deliver outstanding customer interaction through multiple channels, assist in debt resolution, negotiate repayment plans, and ensure compliance with laws and regulations.

The Senior Machine Learning Engineer will design and implement ML pipelines, optimize LLM performance, and collaborate on AI infrastructure for cost-efficient solutions.

The Machine Learning Engineer will build, refine, and optimize AI/ML prototypes while collaborating with teams on technical documentation, deployment, and model integration.

Design, build, deploy, and maintain scalable AI/ML pipelines and production models (including LLMs). Collaborate with data scientists and engineers to optimize model performance, latency, and cost on cloud platforms using MLOps practices, containerization, and CI/CD. Integrate AI capabilities into client and internal applications and monitor models in production.

Lead design, development, and deployment of scalable ML models and pipelines (including LLMs) across the platform. Own full ML lifecycle, influence technical direction, communicate results to stakeholders, and mentor junior engineers.

Lead a team of Senior ML Scientists to enhance automated decision-making in credit risk modeling, optimize data applications, and collaborate across departments.

As a Senior Machine Learning Scientist, you'll improve customer outcomes through automated decisioning using ML and statistical modeling, focusing on credit risk modeling and collaborating with cross-functional teams.

Design, build, and optimize intelligent systems using AI techniques to solve real-world problems. Responsibilities include data processing, model development, and collaboration.

As a Machine Learning Engineer III, you will design, build, and optimize AI systems, utilizing techniques including machine learning and deep learning to solve real-world problems, while collaborating with a global team and communicating complex topics clearly.

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.

Build and operate backend ML platform services for context retrieval, compression, and evaluation to power AI assistants. Own architecture, implementation, observability, and reliability while enabling other teams to integrate reusable APIs and tooling.

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.

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.

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.