Top Machine Learning Jobs in Edinburgh

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.

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.

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.

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.

As a Principal Java Engineer II in the ML Core team, you will build and maintain machine learning components for Elasticsearch, collaborate with engineering teams, and ensure scalable and high-quality code. You'll lead projects from design to implementation while supporting the team and community.

Lead the development and deployment of AI systems, designing scalable ML software and infrastructure while mentoring junior engineers and advising clients.

The Senior Platform Engineer in Machine Learning at Monzo will design, maintain infrastructure for ML models, and work with various cloud technologies.

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

The Senior AI/ML Engineer will design and optimize scalable systems, productionize AI prototypes, solve performance issues, and collaborate with teams on innovative solutions.

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

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

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.

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.

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.

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.

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