Top Machine Learning Jobs in Manchester

Lead the Voice team at Rasa, focusing on mentoring engineers, driving processes, and delivering voice features while maintaining strong communication and async practices.

The Senior Machine Learning Ops Engineer will design and build machine learning operations infrastructure, manage ML pipelines, experiment tracking, model deployment, and collaborate with engineering teams to enhance data and ML processes.

As a Senior Machine Learning Engineer, you will enhance product features, optimize computer vision algorithms, mentor team members, and stay updated with research.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

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 design and delivery of production ML solutions across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring. Partner with product and engineering to build classifiers, regressors, ranking/retrieval systems and rule-based components, implement reliable pipelines, improve reproducibility/testing/observability, and communicate model behavior and trade-offs to stakeholders while shaping team standards and responsible ML practices.

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.

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 an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

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.

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.

Lead end-to-end ML initiatives: integrate and fine-tune models, optimize GPU inference for latency and throughput, build evaluation and monitoring tooling, collaborate on scalable serving systems, and mentor engineers.

Design, build and optimise Python-based AI applications and data storage solutions. Collaborate with clients and teams, enforce code quality, CI/CD, testing practices, and deliver scalable production systems across cloud environments while travelling to client sites.

As an AI/ML Engineer, you will design and develop AI-powered applications, integrate AI features into BPM systems, and collaborate with teams to improve operational efficiency through innovative AI solutions.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

As a Lead Machine Learning Engineer, you'll set technical directions for AI projects, design scalable ML systems, lead project delivery, and mentor a team of engineers while collaborating with clients to achieve their goals.

As a Machine Learning Engineer, you will design, build, and deploy ML systems, manage AI project methodologies, and support delivery with technical expertise, collaborating with cross-functional teams and stakeholders.

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