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As a Staff Machine Learning Engineer, you will be a driving force behind our AI strategy, moving beyond simple models to build complex, production-ready AI agents and scalable systems. You won’t just be prototyping; you will take full ownership of the ML lifecycle—from initial data exploration to architecting the MLOps pipelines that keep our models performing at their peak. This is a high-impact role where you will bridge the gap between cutting-edge research and pragmatic engineering, specifically focusing on automating complex business workflows within our retail and e-commerce ecosystem.
Job Responsibility:
Design, develop, and deploy robust ML systems and multi-model AI agents that solve real-world retail challenges
Lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerisation practices
Build high-performance data pipelines (ETL/ELT) for both training and real-time inference, ensuring our systems are scalable and reliable
Act as a technical lead for the team, mentoring junior engineers, setting engineering best practices, and shaping our long-term technical roadmap
Partner with Product Managers and Data Scientists to translate business ambitions into sophisticated technical requirements
Build models to solve specific problems for our customers and internal teams
Prioritise delivering a working solution that solves a business challenge
Use data and user feedback to refine your technical approach as the problem becomes clearer
Requirements:
Strong proficiency in Python and frameworks like PyTorch, TensorFlow, or Scikit-learn, with a deep understanding of NLP, deep learning, or reinforcement learning
Hands-on experience with modern AI orchestration tools such as LangChain and LangSmith
Proven experience with Docker, Kubernetes, and cloud infrastructure (AWS/GCP/Azure), with a focus on scaling models in production
Expert-level SQL/NoSQL skills and the ability to design high-performance pipelines for massive datasets
A Master’s or PhD in Computer Science or a related field, or equivalent experience leading research-heavy engineering projects
Nice to have:
Direct experience applying AI/ML to retail or e-commerce workflow automation
Experience building systems that involve multiple interconnected ML models or autonomous agents
What we offer:
Flexible working policy
Hybrid approach in our central London office
Enhanced parental leave policy
25 days annual leave + public holidays (and an extra day for every year at EDITED)