AI Inference Infrastructure Engineer

01. ABOUT THE COMPANY

About The Role

03. WHO YOU ARE

• **Systems Engineer**: You have deep experience in systems programming and care about performance at every layer.
• **Performance Optimiser**: You understand how to extract maximum efficiency from hardware — not just make things work.
• **Infrastructure Builder**: You’ve built or contributed to distributed systems where latency and throughput matter.
• **Low-Level Thinker:** You’re comfortable working close to hardware — memory, kernels, execution pipelines.
• **Pragmatic Engineer:** You avoid unnecessary abstractions and focus on what actually improves performance.
• 04.

Responsibilities

• **Core Engine Development**: Design and implement low-level runtime systems (Rust/C) to manage model execution, memory allocation, and request batching across distributed compute.
• **Hardware-Aware Optimisation**: Develop and optimise tensor operations and custom kernels (CUDA, Triton) to maximise hardware utilisation.
• **Inference Performance**: Implement advanced inference techniques such as continuous batching, speculative decoding, and paged attention — tailored to our architecture.
• **Decentralised Orchestration:** Design routing and load balancing systems across geographically distributed nodes to ensure availability and efficiency.
• **Autonomous Infrastructure:** Build fully automated deployment and recovery systems — ensuring zero manual intervention and self-healing network behaviour.
• 05.

Requirements

• Strong experience in systems programming (Go, Rust, or C/C++).
• Proven experience working with performance-critical systems.
• Deep understanding of GPU programming (CUDA, ROCm) and hardware-level optimisation.
• Strong knowledge of deep learning architectures (Transformers, Mamba) and tensor execution.
• Experience building distributed systems with high concurrency and low latency.
• Ability to work close to the hardware and optimise execution pipelines.
• Strong problem-solving skills and attention to performance bottlenecks.

06. WHAT WE OFFER

• Real ownership and direct impact on a global AI infrastructure product
• Fast execution, low bureaucracy, and a highly collaborative, idea-driven team
• Exposure to cutting-edge AI, distributed systems, and hardware-level optimisation
• Competitive salary with performance-based incentives
• 24 days annual leave, plus public holidays
• Health insurance
• Modern office in Yas Creative Hub
• Continuous learning through real-world problem solving — not just theory
• The opportunity to shape what you’re working on and influence product direction
• A diverse, open-minded team where ideas are genuinely heard