AI & ML Engineer

Overview

As AI & ML Engineer you will design, build and deploy production-grade AI/ML solutions that scale across the business. You will collaborate with Data, Product and engineering teams to deliver reusable platforms, services and best practices. You tackle end-to-end development—from discovery to monitoring—focusing on safe, scalable AI in a fast-growing beauty company. This role blends technical depth with product sense to enable impactful, measurable AI initiatives. Join a mission-driven, innovative team accelerating AI adoption across the business.

Pay / Benefits

• 25 days holiday (plus bank holidays)
• Birthday leave
• Pension and life assurance
• Medicash and Employee Assistance Program
• Regular social events
• Dog-friendly days and spaces

Responsibilities

• Design and implement agentic systems using RAG, grounding, prompt engineering, and orchestration on a GCP-first stack
• Build and maintain production ML pipelines and services for non-GenAI use cases (e.g., recommender systems, customer segmentation models, marketing optimisation)
• Develop APIs and microservices for AI/ML solutions with security, scalability, and observability
• Implement CI/CD for ML services, IaC (Terraform), and monitoring for drift and performance
• Establish guardrails for safe AI usage including prompt security and privacy/compliance
• Contribute to reusable components, documentation and engineering best practices across the organisation
• Collaborate with data engineers, data scientists, frontend/backend engineers, and product managers
• Evaluate new AI technologies and provide recommendations for build/buy/configure decisions

Key requirements

• Strong Python engineering skills (FastAPI, testing, typing)
• Cloud-native development experience (GCP preferred)
• Hands-on experience with GCP Vertex AI or equivalent (SageMaker, Azure ML)
• Experience with agent orchestration frameworks (LangChain, LangGraph, ADK)
• Solid understanding of MLOps: CI/CD, IaC (Terraform), experiment tracking, model registry, monitoring
• Production deployment/operation of ML systems (batch and real-time)
• Knowledge of RAG architectures, prompt engineering, guardrails and evaluation
• Experience developing agentic capabilities (agent skills, MCP servers, tool usage)
• Security, privacy, governance (IAM, secrets, PII handling)
• Strong communication with technical/non-technical stakeholders
• Interest in evaluating new AI tech and contributing to build/buy/configure decisions
• Bachelor’s or Master’s degree in Computer Science/Engineering or demonstrable relevant experience
• Knowledge of vector databases and retrieval strategies (nice-to-have)
• Experience with recommender systems and ranking models (nice-to-have)
• Familiarity with LLM evaluation tools (RAGAS, TruLens, LangSmith, Arize)
• Cloud networking and platform infrastructure knowledge (nice-to-have)
• Experience in e-commerce or retail environments (nice-to-have)

• Effective communication
• Collaboration with cross-functional teams
• Curiosity about new AI technologies
• Python (FastAPI)
• GCP Vertex AI and cloud-native platforms
• MLOps tooling (CI/CD, IaC Terraform, model registry)

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