Top Machine Learning Jobs in Edinburgh

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

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

The role involves designing AI-driven solutions for robotics and lab automation, optimizing machine learning models, and collaborating on automated workflows.

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.

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.

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.

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.

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.

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.

The Staff Machine Learning Engineer will lead the execution of ML systems, ensuring reliability and scalability while collaborating with cross-functional teams to deliver high-quality AI solutions.

The VP of Research, Machine Learning will lead the research direction for AI systems, focusing on intelligence design, evaluation frameworks, and advanced machine learning techniques while ensuring real-world applicability.

The Senior Machine Learning Engineer will build core ML systems, handle data preparation and iteration, debug model issues, and ensure reliable production performance while mentoring other engineers.

As Technical Lead, you'll own ML system execution, manage data pipelines, model deployment, and ensure performance under real-world conditions while collaborating with the team.

The role involves building end-to-end production-grade ML systems, optimizing pipelines, integrating models into applications, and maintaining data systems.

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 Machine Learning Engineer will design, build, deploy AI solutions, collaborating with cross-functional teams and ensuring maintainability and scalability of ML systems.

The Senior Machine Learning Engineer will develop machine learning solutions for online gaming platforms, improving security and user experience through data-driven decisions, while collaborating cross-functionally.

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.

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.

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