Nicoll Curtin
Senior ML Engineer
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We’re hiring for a fast-growing, AI-first organisation operating within the insurance sector, focused on building a next-generation intelligent assistant designed to automate complex, real-world workflows and decision-making. The product sits at the intersection of applied machine learning and practical utility, with a strong emphasis on reliability, long-running processes, and delivering meaningful outcomes for everyday users. Backed by a global digital insurance group, the team combines deep technical expertise with a clear commercial focus, working on systems intended to scale across multiple markets.
This is a high-impact opportunity for a Senior Machine Learning Engineer to take ownership of production-grade systems and play a key role in shaping a product that relies on long-horizon reasoning, persistent context, and real-world execution.
Permanent
Remote (must be UK based)
ILR / EU Passport / UK Citizenship required
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What You’ll Be Doing
- Designing and building core ML systems powering intelligent, proactive AI products
- Owning the full lifecycle from data preparation and training through to evaluation, deployment, and iteration
- Turning advanced ML research into scalable, reliable production systems
- Debugging model behaviour and system performance using real-world production signals
- Collaborating closely with product, research, and engineering teams to deliver measurable user impact
- Mentoring other engineers and contributing to a high-performance technical culture
What We’re Looking For
- Strong experience building and deploying ML systems used in production environments
- Deep understanding of how modern ML models behave in real-world settings
- Strong programming skills in Python, with hands-on experience in PyTorch and/or JAX
- Experience working with GPU-based training and inference systems
- A mindset focused on ownership, execution, and delivering practical outcomes
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Tech Environment
- Python
- PyTorch / JAX
- GPU-based training and large-scale inference systems
- Production-grade, real-time ML infrastructure
Success Looks Like
- ML systems consistently meeting targets for accuracy, latency, and reliability
- Scalable and maintainable training, inference, and data pipelines
- Continuous improvement driven by real-world usage and feedback
- Raising the technical standard across the team through strong engineering practices
Why Join
- Work on cutting-edge applied AI with clear, real-world impact
- Join a high-calibre, hands-on team with strong ownership and accountability
- Operate in a fast-moving environment that values shipping and iteration
- Opportunity to help shape AI systems deployed at global scale
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