Machine Learning Engineer Data Science

New Yesterday

As Opus 2 continues to embed AI into our platform, we need robust, scalable data systems that power intelligent workflows and support advanced model behaviours. Youll architect and implement the pipelines and infrastructure that allow our AI features to operate reliably and efficiently in production, whether extending existing systems or building new foundations. Experience in processing large volumes and varieties of structured text data. Experience with legal documents would be a bonus.
Collaborate closely with product, datascience, and platform teams to align data systems with evolving model and workflow needs.
Were here to ship real AI features, not experiments. We want engineers who can help squads own the full lifecycle: plan, build, test, deploy, and maintain AI powered functionality as part of their delivery flow. Were building now and are hoping to find our next teammate to start as soon as they are available.
You thrive on building data systems that enable advanced features, not just move bytes around.
You are excited by newer patterns like hybrid and graph-based retrieval (Graph RAG).
5+ years of experience working in a software engineering role.
~3+ years of experience building and maintaining production-grade data infrastructure, preferably for ML/AI use cases with 1+ years working with LLMs.
~ Proficiency with AWS data tooling and cloud-native services; Experience with vector databases and embedding pipelines.
~ Familiarity with or interest in graph-based data models and Graph RAG architectures is a strong plus.
~ Working knowledge of Java and TypeScript environments, especially for integration and debugging.
~ Opus 2 is a global leader in legal software and services, trusted partner of the worlds leading legal teams. All our achievements are underpinned by our unique culture where our people are our most valuable asset. Contributory pension plan.
~26 days annual holidays, hybrid working, and length of service entitlement.
~ Health Insurance.
~ Loyalty Share Scheme.
~ Employee Assistance Programme.
~ Electric Vehicle Salary Sacrifice.
~ Cycle to Work Scheme.
~ A day of leave to volunteer for charity or dependent cover.
~ Accessible and modern office space and regular company social events.

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Location:: London
Job Type:: FullTime