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Senior Data Scientist (ML Platform)
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Senior Data Scientist (ML Platform & Production)
Senior individual contributor role at a fast-scaling, AI-first software business
Own the full data-to-production lifecycle across ML models, agents, and platform infrastructure
Belfast based, hybrid with an async-friendly global team
Salary: competitive, reflecting experience, with equity
UK work authorisation required
About the Company
Our 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 Role
A 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.
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Key Responsibilities
- Scale and harden existing deep learning models from R&D into reliable, observable production systems
- Build and maintain reproducible pipelines for training data, feature generation, and embeddings
- Own reliability, monitoring, and incident response for ML models and agents in production, including CI/CD, versioning, canary deployment, and rollback
- Build observability into ML services covering latency, error rates, drift detection, and quality regressions
- Contribute to the one to two-year roadmap for the data and ML platform
- Set engineering standards, conduct design reviews, and mentor engineers on production-grade practices
- Work closely with infrastructure and release teams across a globally distributed, async-first team
What You'll Need
Essential:
- Strong academic foundation in Applied Mathematics, Physics, Astrophysics, or a hard STEM discipline
- 5 or more years across data engineering and ML production engineering, including 2 or more years in MLOps or ML production systems
- Proven track record deploying and maintaining live, customer-facing ML systems at scale in production environments
- Hands-on production experience with Google Cloud Platform, specifically Vertex AI and BigQuery, or equivalent AWS or Azure experience
- Strong experience building data and feature pipelines for ML training
- Experience with ML pipeline tooling such as MLflow, Kubeflow, or Vertex AI, and CI/CD for model lifecycle management
- Experience with Docker, Kubernetes, and cloud infrastructure
- Proven track record owning production incidents including detection, mitigation, and rollback
- Strong Python, Go, or Java fundamentals
- Experience mentoring engineers and influencing technical direction
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Desirable:
- Experience operating LLM or agent-based systems in production including LLMOps
- Direct experience partnering with data scientists on feature engineering or model training
- Master's or PhD in a relevant STEM field
Why Apply?
- Competitive salary plus equity, with package tailored to UK, NI, or European candidates
- Work directly with the Head of Data Science on mission-critical production systems for Fortune 500 clients
- Hands-on, intellectually driven team that debates ideas openly and challenges assumptions constructively
- Async-friendly culture with approximately three syncs per week, designed to protect deep focus and work-life balance
- Fast-moving startup environment with full operational autonomy and no corporate inertia
- Belfast based with a globally distributed, elite AI engineering team behind you
Interested?
For a confidential conversation about this opportunity, connect with Justin Donaldson on LinkedIn or submit your CV via the link below.
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