Machine Learning Jobs in Edinburgh

• London
• Hybrid
• £65,000 – £145,000 pa

Engineers at all levels build and scale the shared tooling and infrastructure behind the institute's AI safety research, from Inspect plugins and large-scale evaluation systems to model hosting and secure proxy infrastructure. Work spans open-source collaboration, supporting research teams with custom setups, and hardening infrastructure for frontier model evaluations.

Inspect

• London
• Hybrid
• Senior
• Permanent

Drive safety research for agentic LLMs, focusing on data generation, post-training algorithms and evaluation methods so models that access external tools and act in the world remain fair, trustworthy and secure. Work with cross-functional ML, data annotation, product and policy teams on a small, autonomous team, requiring strong statistics, software engineering and Python/PyTorch skills.

PyTorch · TensorFlow · JAX

• Edinburgh
• Hybrid
• Lead
• Permanent

Builds machine learning recommendation systems that match job seekers to roles and recruiters to talent across Amazon Jobs and internal hiring platforms. Works on representation learning, reinforcement learning and probabilistic modelling at global scale, with a focus on fairness and explainability, alongside engineers, scientists and product managers through the full development lifecycle.

• London
• Hybrid
• £65,000 – £145,000 pa

The Chem Bio team researches, evaluates and mitigates chemical and biological risks from frontier AI systems, running capability evaluations, building benchmarks and datasets, and developing safeguards and monitoring methods. Findings are shared with frontier AI companies, UK officials and allied governments to inform deployment and policy. The role is open to research engineers and scientists at all seniority levels, with appointment conditional on obtaining UK Government Developed Vetting clearance.

• Stirling
• Senior · manages people

Designs, builds and optimises scalable data pipelines in Azure Databricks, Spark and Python to support actuarial modelling and assumption setting. Applies machine learning and advanced analytics where they add measurable value, drives process reengineering and embeds audit and risk controls. Also guides and reviews the work of junior team members and shapes data standards and best practice.

Azure Databricks · Spark · PySpark +1

• London
• Hybrid · 3 days in office
• Senior

Senior individual contributor building the shared platform, tooling and infrastructure for an interdisciplinary chem-bio research team, including LLM-based agent systems and evaluation frameworks. Works closely with researchers to translate varied needs into maintainable Python systems, while contributing to engineering standards and mentoring peers without line management.

AWS · Kubernetes · Slurm +2