Lead ML Engineer - Search & Recommendation (London Onsite)

Jingdong Development France; United Kingdom; Presencial; GBP 90 000 - 140 000; Tempo integral

Resumo da oferta

JD.com is seeking a Machine Learning Team Lead for our London office. You will lead a team of algorithm engineers, designing and deploying advanced search and recommendation models to enhance user experience and drive growth in a fast-paced, global e-commerce environment.

You will balance hands-on modeling with leadership, collaborate with product and engineering, and stay ahead of ML/NLP advances to deliver high-impact solutions.

Qualificações

• Master's degree or higher in CS, mathematics, or a related field with ML/NLP focus.
• 6+ years in search, recommendation, or advertising systems; at least 2 years in leadership.
• Proficiency in ML, NLP and deep learning with TensorFlow or PyTorch.
• Strong programming in Python, C++, or Java with solid data structures knowledge.
• Excellent communication in English and Chinese.

Responsabilidades

• Lead and mentor a team of algorithm engineers, providing technical direction and growth support.
• Design, develop, and optimize search and recommendation algorithms for personalization and engagement.
• Oversee traffic distribution strategies to meet diverse business needs in search/recommendation.
• Drive experiments and evaluation of models for scalable deployment and performance improvements.
• Stay current with ML/NLP advances and apply them to real-world challenges.
• Work onsite in London.

Conhecimentos

Machine learning

NLP

Leadership

Python

C++

Java

TensorFlow

PyTorch

English

Chinese

Formação académica

Master's degree in CS

Ferramentas

TensorFlow

PyTorch

Scikit-learn

Descrição da oferta de emprego

JD.com is seeking a Machine Learning Team Lead for our London office. You will lead a team of algorithm engineers, designing and deploying advanced search and recommendation models to enhance user experience and drive growth in a fast-paced, global e-commerce environment.

You will balance hands-on modeling with leadership, collaborate with product and engineering, and stay ahead of ML/NLP advances to deliver high-impact solutions.