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JD.COM

High Availability / AI Infrastructure Software Engineer

London
Posted 7 days ago
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Who We Are

At JD.com, also known as JINGDONG, we are building one of the world’s most trusted technology and supply chain ecosystems. What started as a bold idea in China has evolved into a NASDAQ-listed, Fortune 44 global enterprise serving over 700 million active customers. Powered by advanced logistics, innovative technology, and a commitment to integrity, JD.com operates across retail, logistics, technology, property and more, creating solutions that make everyday life smarter, faster, and more connected.

Our Global Reach

JD.com is expanding its international footprint through a digitally intelligent, cross-border supply chain and world-class logistics network, supported by platforms such as Joybuy, which brings trusted products to customers worldwide. Today, our teams operate across China, the U.S., U.K., Netherlands, France, Germany, Spain, Brazil, Hungary, Japan, South Korea, Australia, Thailand, Vietnam, Malaysia, Indonesia, Saudi Arabia, the UAE and beyond, reaching customers in every corner of the world.

Learn more about who we are and what we do: https://corporate.jd.com/

What We Offer

Joining JD.com means becoming part of a company where people, innovation, and impact go hand in hand. We offer a competitive salary, a great location, and a supportive, people-first culture where your growth truly matters. With access to global projects, learning opportunities, and an inclusive environment that values every voice, you’ll have the space to shape the future with us.

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About The Team

You’ll be joining the JD.com team, which values collaboration, ownership, and a commitment to delivering high-quality results in a fast-paced, dynamic environment.

Responsibilities & Objectives

  • Participate in building the AI Infrastructure technical architecture for JD.com's cross-border e-commerce; develop and drive the implementation of architectural standards.
  • Lead the top-level architectural design for complex technical projects; evaluate critical technical issues and break down project execution steps.
  • Scheduling System Optimisation: Participate in the R&D of the intelligent computing operating system; Optimize GPU resource scheduling capabilities within Kubernetes or Ray.
  • High Availability Assurance: Resolve GPU cluster fault recovery (Fault Tolerance) and elastic fault tolerance (elastic checkpointing).
  • Efficiency & Observability: Build cluster efficiency evaluation models; precisely measure computing resource utilisation (MFU/HFU). Track industry trends and cutting-edge technologies; introduce new technologies and solutions to the team based on actual business needs.

Requirements

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  • 3+ years of experience in AI infrastructure, distributed systems, High-Performance Computing (HPC), or large-scale cloud platform development.
  • Proficient in Python, with a solid foundation in data structures and algorithms, and a rigorous coding style.
  • Bonus points: Deep understanding of the underlying source code and runtime mechanisms of PyTorch, Megatron-LM, or DeepSpeed.
  • Bonus points: Proficient in GPU/NPU architecture, with hands-on development and optimization experience in CUDA C/C++ or Triton.
  • Strong self-drive and technical curiosity; ability to proactively track the most cutting-edge AI Infra trends in the industry.
  • Bachelor’s degree or higher in Computer Science, Electronic Information, Automation, Applied Mathematics, or related fields; experience in cross-border e-commerce is highly preferred.

At JD.com, we’re committed to building a diverse and inclusive workplace where everyone can thrive. We’re proud to be an equal opportunity employer and make all employment decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, veteran status, or any other protected characteristic.

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Skills

AI Infrastructure
Distributed Systems
High-Performance Computing
Cloud Platform Development
Python
Data Structures
Algorithms
PyTorch
Megatron-LM
DeepSpeed
GPU Architecture
NPU Architecture
CUDA
C++
Triton
Kubernetes

Location

London, England, United Kingdom

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