Senior Machine Learning Engineer

In this role you will own end-to-end delivery of ML, GenAI and multi-agent solutions for complex payments and banking operations. You will deploy secure, scalable ML services via APIs and batch/streaming patterns while building reusable components and ensuring safety and monitoring. You will mentor engineers, communicate with stakeholders, and translate model outputs into actionable decisions. This position sits at the intersection of product, risk, and technology to advance production AI at scale.

• Own end-to-end delivery from problem framing to production rollout
• Build ML, GenAI and multi-agent solutions with evaluation, safety, and monitoring
• Set production patterns: containerisation, CI/CD, automated testing, model and prompt registries, rollback
• Deploy secure, scalable ML and LLM services via APIs, batch, streaming and event-driven patterns
• Create reusable components: feature engineering, evaluation harnesses, agent frameworks, orchestration, memory management
• Mentor engineers and data scientists through code and design reviews
• Turn model outputs into decisions and trade-offs for non-technical stakeholders
• Maintain model cards, runbooks and audit-ready documentation

• Master's in a quantitative field, or equivalent experience
• Strong ML fundamentals and applied data analysis
• Production ML at scale: monitoring, drift, reliability, incident management
• Strong Python engineering: modular OO design, testing, performance tuning
• MLOps and LLMOps: training and serving patterns, feature stores, orchestration
• Offline and online evaluation, with guardrails
• Regulated environment experience: model risk, controls, privacy, security
• Strong stakeholder management

• stakeholder management
• mentoring and people skills
• communication of technical concepts to non-technical audiences
• LLMs and agentic workflows
• MLOps and LLMOps
• PyTorch, TensorFlow, scikit-learn, pandas, SciPy, statsmodels