AI Research Engineer – Networking & Inference Gateway - Intern

About Huawei

Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home and organization for a fully connected, intelligent world.

At Huawei, innovation focuses on customer needs. We invest heavily in basic research, concentrating on technological breakthroughs that drive the world forward. We have more than 180,000 employees, and we operate in more than 170 countries and regions.

About The Irc

Huawei Ireland Research Centre (IRC) mission is to position Huawei as a recognized technology leader and a global provider of information and communications technology (ICT) solutions. To achieve this we are building an industry-recognized multi-discipline Research Centre of experts with focus on medium-term to long-term issues. The IRC will work closely with an open innovative ecosystem with Huawei customers to address real-world issues. The IRC will also engage with key European universities to build a basic research capability to support Huawei technical projects.

About The Role

We are looking for an Intern AI Research Engineer to work on Huawei Cloud Inference Serving Team. Join us to push the boundaries of what's possible in Distributed AI inference performance and reliability. In this role, you won't be just writing code; you will be also solving some of the most complex and exciting challenges in distributed Inference serving. Your work will directly impact the latency, efficiency, security and stability of our cloud-based AI services.

As part of our networking and gateway infrastructure focus, you'll work on key challenges around low-latency request handling, intelligent load balancing across distributed resources, and building highly reliable, observable systems that can scale to handle massive concurrent traffic while maintaining strict performance and reliability requirements.

Responsibilities

• Develop and optimize core components of high-performance, low-latency AI inference gateway systems
• Implement request routing and load balancing mechanisms to efficiently distribute traffic across available resources
• Build networking optimizations and connection management systems to minimize latency and maximize throughput
• Create observability and monitoring tools for real-time performance analysis and system health tracking
• Develop REST and gRPC APIs that integrate seamlessly with existing ML infrastructure
• Write well-tested, maintainable code and participate in code reviews with the team

Requirements

• Currently pursuing BS/MS in Computer Science, Computer Engineering, or related field
• Strong programming fundamentals with experience in systems languages (Rust, Go, C++, or Java)
• Solid understanding of networking concepts including HTTP, TCP/IP, load balancing, and distributed systems
• Experience with concurrent programming, async patterns, and multi-threaded applications
• Knowledge of API development, web services, and service-oriented architectures
• Understanding of performance optimization techniques and system profiling

Preferred

• Strong candidates would understand transformer architectures and internals, and might have hands-on experience with model serving infrastructure, quantization techniques or building APIs around large language models
• Hands on experience with Rust programming language and its async ecosystem
• Familiarity with gRPC, Protocol Buffers, and high-performance RPC frameworks

What You'Ll Gain

This internship provides deep hands-on experience with modern systems programming and large-scale distributed networking infrastructure. You'll work closely with experienced engineers who will guide you through complex technical challenges in building production AI serving systems. The role offers valuable exposure to cutting-edge technologies like Rust async programming, high-performance networking, and observability systems, giving you skills that are highly valued across the industry. You'll contribute to real systems that handle production traffic while learning best practices in reliability, performance, and scalable system design.

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