Full‑Stack Machine Learning Engineer

About the Role

Build and deploy ML‑powered services, tools, and full‑stack applications supporting fraud and identity analytics. Work across backend services, model‑serving pipelines, and user interfaces.

Key Responsibilities

• Develop ML inference APIs, microservices, and data/feature pipelines.
• Build full‑stack tools to support model evaluation and transparency.
• Integrate ML models into real‑time production systems.
• Implement automated training, monitoring, and evaluation workflows.
• Use and contribute to AI‑assisted development tools.
• Own DevOps and security standards for assigned services.
• Collaborate with data scientists, architects, and QA.

Required Experience

• 4+ years software engineering (backend, full‑stack, or ML).
• Strong Python and Java.
• Snowflake or similar data‑platform experience.
• Familiarity with ML model serving and feature engineering.
• Strong ownership and independent execution.
• Working knowledge of DevOps and secure engineering.

Preferred Experience

• LLMs, embeddings, or vector databases.
• Behavioural, graph, or anomaly detection models.
• dbt, Snowpark, or Snowflake ML.

Benefits

• Generous holiday allowance with the option to buy additional days
• Health screening, eye care vouchers and private medical benefits
• Wellbeing programs
• Life assurance
• Access to a competitive contributory pension scheme
• Save As You Earn share option scheme
• Travel Season ticket loan
• Electric Vehicle Scheme
• Optional Dental Insurance
• Maternity, paternity and shared parental leave
• Employee Assistance Programme
• Access to emergency care for both the elderly and children
• RECARES days, giving you time to support the charities and causes that matter to you
• Access to employee resource groups with dedicated time to volunteer
• Access to extensive learning and development resources
• Access to employee discounts scheme via Perks at Work

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