Top Machine Learning Jobs in Edinburgh

As a Machine Learning Engineer, you will develop production-ready solutions, enhancing financial data and collaborating with product teams. Responsibilities include optimizing algorithms and analyzing user insights.

The Machine Learning Engineer will design and develop an AI platform for scientific research, collaborating with teams to enhance automation and data analysis.

Assist in pioneering research in AI and ML at Sahara AI, focusing on innovative model development and collaboration with tech leaders.

The Senior Machine Learning Engineer will design and productionize ML systems, maintain data pipelines, collaborate with cross-functional teams, and mentor junior engineers.

The Senior Machine Learning Engineer will develop AI/ML solutions, optimize pipelines, mentor juniors, and contribute to product development in a collaborative environment.

As Engineering Manager, you will lead multiple teams in vegetation modeling and data ingestion to improve product delivery and team performance.

Lead the development of machine learning models for account takeover detection, collaborating with teams to implement robust solutions and improve production models.

Design and implement AI infrastructure for intelligent functionality. Collaborate across teams to scale AI impact globally, ensuring AI systems are robust and production-ready.

Join the ML Platform Team to develop a high-scale compute and data platform, supporting AI model training and infrastructure management. Collaborate with researchers and data scientists, focusing on ML and DevOps practices.

The AI/ML Specialist Solutions Architect designs AI solutions for clients, resolves technical challenges, and manages scalable AI deployments.

As a Senior/Staff ML Engineer, you will experiment with training large language models, improve agentic task infrastructure, and utilize data mining techniques.

The Staff ML Engineer / ML Team Lead at Zencoder will lead the development of AI-driven solutions, focusing on AI pipelines and models for code generation and refinement. Responsibilities include creating embedded AI agents, collaborating with teams, testing solutions, and staying updated on industry trends.

You will design and build scalable, observable LLM-powered backend services, integrate observability tools, and collaborate with data scientists to improve ML workflows.

Design and build AI infrastructure for various applications, ensuring robustness and reusability while collaborating with different teams.

The AI Data Engineer will develop scalable data ingestion pipelines and optimize distributed architectures for generative video models using high-quality data.

The Senior ML Engineer will lead content understanding projects, develop NLP models, build data pipelines, and ensure system reliability while collaborating with teams to translate business needs into technical solutions.

Lead the development and scaling of ZOE’s photo logging AI product. Collaborate with engineers and data scientists to improve model performance and solve backend challenges.