Permutable builds AI systems that analyse global news, market and proprietary data to produce market intelligence and systematic signals for financial institutions.
Work connects developments across energy, commodities, economic policy and geopolitics to the assets and markets they influence.
Responsibilities
Build production LLM pipelines: develop systems spanning data preparation, model training and fine-tuning, evaluation, deployment and ongoing monitoring.
Improve model performance: use Python and in-house GPU infrastructure to experiment with model architectures and fine-tuning approaches, assessing quality alongside latency and compute requirements.
Make evaluation part of development: build repeatable evaluations, investigate failure cases and use the results to guide model and pipeline improvements.
Orchestrate data and model workflows: build and maintain Apache Airflow pipelines, with monitoring, retries and clear approaches to failure recovery.
Deploy and operate AI services: work with AWS services including Lambda, ECS/EKS, S3 and Redshift, supported by Docker, GitHub Actions and Pulumi.
Take responsibility for what you build: follow your work through deployment, monitor its behaviour in production and resolve problems with the team.
Contribute to engineering decisions: bring ideas, test assumptions and help choose practical approaches to the next technical challenge.
Requirements
At least two to three years of professional AI/ML engineering experience, or equivalent experience delivering substantial, relevant systems.
Strong Python skills and software engineering fundamentals, including maintainable code, testing, debugging and version control.
Hands-on experience building, training or fine-tuning machine learning models, with a clear understanding of how to evaluate their performance.
Experience taking models or AI pipelines into production and understanding what is needed to keep them working reliably.
Familiarity with MLOps practices, including CI/CD, containerisation, automated testing and monitoring.
A grounding in computer science, engineering, machine learning, mathematics or a related discipline.
Curiosity, initiative and the ability to work through unfamiliar problems.
Conditions
Work together in Vauxhall office at least three days each week.
Equity options give you a stake in Permutable’s long-term growth and success.
Regular staff socials, offsites, sports events and office treats.