Top Machine Learning Jobs in Edinburgh

Research and develop machine learning algorithms for automation, collaborating with product teams to implement scalable models in a dynamic environment.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

The Senior Machine Learning Engineer will enhance the RAG platform by delivering AI solutions, collaborating with teams on product features, mentoring, and maintaining system stability.

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

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

The role focuses on transforming language models into impactful products, involving fine-tuning models, designing datasets, and evaluating performance, while collaborating with various teams.

The role involves fine-tuning models, designing architectures, building evaluation pipelines, and collaborating on AI product features for a global audience.

The Tech Lead will architect and implement AI systems, oversee model integration and ensure compliance with security standards while collaborating with teams on scalable solutions.

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.

As a Machine Learning Engineer, you'll develop ML and GenAI solutions, deploy algorithms, monitor performance, and foster a collaborative data culture while identifying opportunities for impact.

As a Machine Learning Engineer, you will develop and implement ML algorithms and GenAI solutions, productionize algorithms, and foster a collaborative data science culture while identifying impactful opportunities across products.

Research and develop machine learning models for cybersecurity applications, integrating outcomes into products and collaborating with engineers.

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 ML Engineer will enhance fine-tuning methodologies, research inference optimization techniques, and re-implement LLM architectures focusing on distributed training and efficiency.

The Senior DevOps Engineer will design, implement, and optimize ML/AI pipelines using Azure Databricks, ensuring AI models are production-ready and scalable.

As a Senior Machine Learning Engineer, you'll develop and maintain APIs and pipelines for AI evaluation, ensuring reliability and scalability for product teams.

Lead Machine Learning initiatives focusing on fraud prevention and customer personalization, fostering collaboration across teams to enhance banking experiences through advanced ML models.

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

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 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.

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

Research and develop AI/ML models for handwriting recognition and related technologies, collaborating with a multidisciplinary team to deliver innovative features.