Senior Machine Learning Scientist improving customer and business outcomes using ML and statistical modeling. Working with experienced team and involved in end - to - end model development.
About the role
- Machine Learning Engineer developing LLM-powered systems at Trainline. Designing predictive ML systems, collaborating with cross-functional teams on AI initiatives.
Responsibilities
- Design and build LLM-powered agentic systems using frameworks such as LangGraph and LangChain
- Develop and optimise RAG pipelines, tool-using agents, and multi-step workflows with appropriate guardrails and validation
- Monitor and evaluate model and agent performance using appropriate ML metrics (e.g. precision, recall) and production monitoring tools
- Maintain and improve traditional ML models alongside newer GenAI capabilities
- Partner closely with stakeholders to frame problems, define success metrics, and deliver measurable business impact
- Take ownership of technical initiatives, driving delivery from ideation through to production and iteration
- Contribute to our wider AI & ML community through knowledge sharing, experimentation, and continuous learning
Requirements
- Strong experience in Machine Learning with solid foundations in the ML lifecycle, evaluation methodologies, and statistical thinking
- Hands-on experience with GenAI, Large Language Models, and NLP techniques, including RAG and agent-based systems
- Proficient in Python and common ML libraries (e.g. PyTorch, scikit-learn, XGBoost, Pandas)
- Experience deploying and operating ML or AI systems in production environments
- Understanding of ML Ops and DevOps principles (e.g. Docker, CI/CD, infrastructure as code)
- Experience working with cloud infrastructure (preferably AWS)
- Take ownership of technical tasks and proactively drive solutions forward
Benefits
- Private healthcare & dental insurance
- Generous work from abroad policy
- 2-for-1 share purchase plans
- EV Scheme to further reduce carbon emissions
- Extra festive time off
- Excellent family-friendly benefits
- Clear career paths
- Transparent pay bands
- Personal learning budgets
- Regular learning days
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