Senior Data Scientist (ML Platform)

Senior Data Scientist (ML Platform & Production)Senior individual contributor role at a fast-scaling, AI-first software businessOwn the full data-to-production lifecycle across ML models, agents and platform infrastructureBelfast based, hybrid with async-friendly global teamSalary: competitive, reflecting experience, with equityUK work authorisation requiredAbout the CompanyOur client is a fast-scaling AI software business powering enterprise automation for Fortune 500 clients including major names across financial services and healthcare technology. Their small, elite Data Science and AI team builds and deploys cutting-edge ML and agentic AI systems at scale, with a culture built around intellectual curiosity, hands-on leadership and pragmatic startup thinking. Leaders stay close to the code, debate ideas openly and move fast without corporate inertia. This is a team where exceptional engineers thrive.The RoleA newly created senior role bridging the gap between machine learning research and high-scale production systems. You will partner closely with the Head of Data Science to harden existing production models, build reliable data and feature pipelines, and own the full MLOps lifecycle from deployment through to monitoring, incident response and continuous improvement. Alongside delivery, you will establish observability standards, lead deployment practices and contribute to platform roadmap development. This role suits someone equally comfortable in the weeds of a training pipeline and setting technical direction for a growing platform.Key ResponsibilitiesScale and harden existing deep learning models from R&D into reliable, observable production systemsBuild and maintain reproducible pipelines for training data, feature generation and embeddingsOwn reliability, monitoring and incident response for ML models and agents in production, including CI/CD, versioning, canary deployment and rollbackBuild observability into ML services covering latency, error rates, drift detection and quality regressionsContribute to the one to two year roadmap for the data and ML platformSet engineering standards, conduct design reviews and mentor engineers on production-grade practicesWork closely with infrastructure and release teams across a globally distributed, async-first teamWhat You'll NeedEssential:Strong academic foundation in Applied Mathematics, Physics, Astrophysics or a hard STEM discipline5 or more years across data engineering and ML production engineering, including 2 or more years in MLOps or ML production systemsProven track record deploying and maintaining live, customer-facing ML systems at scale in production environmentsHands-on production experience with Google Cloud Platform, specifically Vertex AI and BigQuery, or equivalent AWS or Azure experienceStrong experience building data and feature pipelines for ML trainingExperience with ML pipeline tooling such as MLflow, Kubeflow or Vertex AI, and CI/CD for model lifecycle managementExperience with Docker, Kubernetes and cloud infrastructureProven track record owning production incidents including detection, mitigation and rollbackStrong Python, Go or Java fundamentalsExperience mentoring engineers and influencing technical directionDesirable:Experience operating LLM or agent-based systems in production including LLMOpsDirect experience partnering with data scientists on feature engineering or model trainingMaster's or PhD in a relevant STEM fieldWhy Apply?Competitive salary plus equity, with package tailored to UK, NI or European candidatesWork directly with the Head of Data Science on mission-critical production systems for Fortune 500 clientsHands-on, intellectually driven team that debates ideas openly and challenges assumptions constructivelyAsync-friendly culture with approximately three syncs per week, designed to protect deep focus and work-life balanceFast-moving startup environment with full operational autonomy and no corporate inertiaBelfast based with a globally distributed, elite AI engineering team behind youInterested?For a confidential conversation about this opportunity, connect with Justin Donaldson on LinkedIn or submit your CV via the link below.