Machine Learning Engineer

Digital Intelligence Engineer

Tech stack: Python, Machine Learning, Statistical Modelling, AI Evaluation, LLMs, Production ML

Remote - Occasional Client Visits

We’re hiring a Digital Intelligence Engineer to help build, deploy, and evaluate intelligent systems for enterprise clients across regulated industries.

This is a hybrid role for someone who is data science first and systems engineering second — combining strong traditional machine learning expertise with the ability to deploy production-grade AI systems and communicate results directly to clients.

The Role:

* Build and deploy intelligent systems for real-world business applications

* Apply statistical analysis, classical machine learning, and experiment design to enterprise problems

* Design and evaluate ML systems using robust performance metrics and validation approaches

* Work across the full lifecycle from modelling through to deployment and scaling

* Lead client conversations around AI evaluation, performance, and system behaviour

* Present data-backed findings and explain technical outcomes to enterprise stakeholders

* Collaborate closely with engineering teams to integrate AI systems into production environments

* Contribute to internal knowledge sharing and AI engineering best practices

What We’re Looking For:

* 5+ years of experience across data science and machine learning with strong software engineering capability

* Strong expertise in traditional ML, statistical analysis, evaluation methods, and experiment design

* Experience building, deploying, and scaling ML systems in production

* Strong Python and applied machine learning experience

* Ability to communicate complex AI concepts clearly to enterprise clients

* Experience delivering real-world business projects using production AI systems

* Comfortable working independently and contributing to technical direction

Nice to Have:

* Experience in regulated industries such as pharma, biopharma, medtech, or financial services

* GAMP experience with ML systems in production

* Experience with LLMs and practical AI applications across business use cases

* Experience with cloud infrastructure, APIs, or ML deployment tooling

Why Join:

* Work on real-world enterprise AI deployments

* High ownership across AI delivery, evaluation, and deployment

* Collaborative, engineering-led environment

* Opportunity to shape how intelligent systems are deployed in regulated industries

* Build AI systems that solve practical business problems in production