Machine Learning Engineer - LLMs & Real-Time Intelligence

Permutable builds AI systems that turn global news, market and proprietary data into market intelligence and systematic signals for financial institutions. The Machine Learning Engineer will take models from experimentation into production, building and evaluating LLM pipelines and operating reliable, real-time AI workflows.

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 our 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