AI Engineer in City of London

About the Role

JD.com is seeking an experienced AI Engineer to join our growing technical team at Joybuy. Joybuy is JD.com’s European full-category online retail brand designed to bring customers a faster, more convenient, and cost-effective shopping experience. Offering same-day and next-day delivery across the UK, Joybuy combines speed, reliability, and affordability to meet the needs of modern shoppers. In this role, you will design, develop, and deploy AI/ML solutions that power Joybuy. You will work at the intersection of machine learning, engineering, and product, building intelligent systems that drive personalisation, search, recommendation, content understanding, and operational efficiency at scale.

Key Responsibilities

• Design, build, and maintain AI/ML models and pipelines for Joybuy's international platform, covering areas such as personalisation, recommendation, NLP/LLM applications, computer vision, and fraud detection.
• Own end-to-end machine learning lifecycle from problem formulation and data exploration to model training, evaluation, deployment, monitoring, and iteration in production.
• Collaborate closely with product managers, software engineers, and data teams across Europe and China to align AI capabilities with business goals and regional market needs.
• Research, adopt, and promote state-of-the-art AI/ML technologies and methodologies, contributing to the team's technical roadmap and architectural vision.
• Build and optimise machine learning infrastructure and tooling, including feature stores, model serving platforms, A/B testing frameworks, and CI/CD pipelines for machine learning.
• Work onsite in Green Park, London.

Minimum Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics, Machine Learning, or a related technical field.
• 3+ years of hands-on experience in building and deploying machine learning models in production environments.
• Strong programming skills in Python, with proficiency in machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Solid understanding of modern machine learning techniques including deep learning, NLP, recommendation systems, or LLMs.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerisation (Docker, Kubernetes).
• Experience with MLOps tooling and practices — model versioning, experiment tracking, CI/CD, A/B testing.
• Proactive, fast learner, and highly collaborative, with strong communication, analytical, and problem-solving skills, capable of independently identifying and resolving complex technical challenges.
• Effective communication skills in English.

Preferred Qualifications

• Work experience in large-scale e-commerce companies or high-traffic consumer-facing platforms.
• Experience with LLM fine-tuning, RAG architectures, or generative AI applications.
• Experience building multilingual or cross-market AI systems for European/global audiences.
• Experience with real-time inference systems, feature engineering at scale, or online learning.
• Publications at top-tier ML/AI conferences (NeurIPS, ICML, KDD, ACL, CVPR, etc.) or significant open-source contributions.
• Effective communication skills in Chinese.

What We Offer:

• A dynamic and challenging work environment in a leading global e-commerce company with a fast-growing international business.
• The opportunity to work with a diverse international team spanning London and Beijing, making a significant impact on JD.com's global AI strategy.
• Competitive salary and benefits package, including health insurance, retirement plans, and performance bonuses.
• Exposure to massive-scale data, complex cross-border e-commerce challenges, and real-world AI problems that impact millions of users.

JD.com is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.