Runtime Engineer (C/C++)

Evollabs; Dubai; On-site; AED 180,000 - 300,000; Full time

Job summary

Evollabs in the UAE is seeking a senior systems software engineer to own and evolve the core runtime architecture that bridges the compiler and high-end AI hardware. You will optimize runtime execution performance and ensure robust memory management across multi-device environments.

The role requires deep experience near hardware, with a focus on latency and throughput, plus strong C/C++ and Python skills. Collaboration with compiler, firmware, and hardware teams is essential for scalable,

Qualifications

• 5-8+ years in systems software, runtime systems, or performance-critical infrastructure.
• Strong proficiency in C/C++ and Python.
• Fundamentals of operating systems, multi-threading, synchronization, memory management, and cache behavior.
• Experience near hardware (GPU/accelerator/driver/firmware).
• Familiarity with command queues, execution engines, and DMA-based systems.
• Understanding of computational graphs, tensor execution, and memory layouts.
• Experience profiling and optimizing latency and throughput in performance-sensitive systems.

Responsibilities

• Own the core runtime architecture bridging the compiler and hardware.
• Ensure runtime execution engine performance and stability.
• Design device memory management for performance and efficiency.
• Collaborate on the command submission and hardware interaction layer.
• Develop concurrency and scheduling model for model execution.
• Build observability tooling: profiling, logging, tracing.
• Make design decisions for long-term scalability and maintainability.

Skills

C/C++

Python

Operating systems

Multi-threading

Hardware interaction

Tensor execution

Performance profiling

Tools

MLIR/LLVM

CUDA

PyTorch/ONNX

XLA

Job description

We are a tech company specializing in the design and development of cutting-edge, customized server hardware solutions optimized for artificial intelligence and machine learning applications. Our mission is to empower businesses and researchers to accelerate their AI initiatives by providing them with high-performance, scalable, and energy-efficient hardware infrastructure.

As a rapidly growing company at the forefront of AI hardware innovation, we are constantly seeking talented and motivated individuals to join our team. We offer a dynamic and challenging work environment, with opportunities to make a significant impact on the future of AI technology.

You'll Collaborate With

• Compiler engineers, firmware & driver engineers, hardware architects, ML framework engineers and performance & validation teams

What You'll Own

• The core runtime architecture that bridges the compiler and the hardware


• Runtime execution engine performance and stability


• Device memory management design and efficiency


• Command submission and hardware interaction layer (in collaboration with firmware/driver teams)


• Concurrency and scheduling model for model execution


• Observability tooling (profiling, logging, tracing) within the runtime


• Technical design decisions that ensure long-term scalability and maintainability

Minimum Qualifications

• 5-8+ years of experience in systems software, runtime systems, or performance-critical infrastructure


• Strong proficiency in C/C++and Python


• Solid understanding of fundamentals of operating systems, multi-threading, synchronization, memory management, and cache behavior


• Experience working close to hardware (GPU, accelerator, driver, or firmware environments)


• Familiarity with command queues, execution engines, and DMA-based systems


• Understanding of computational graphs, tensor execution, and memory layouts


• Experience profiling and optimizing latency and throughput in performance-sensitive systems

Preferred Qualifications

• Experience building or architecting a runtime from scratch


• Familiarity with MLIR, LLVM, or compiler-runtime interfaces


• Experience with one or many from CUDA, ROCm, TensorRT, TVM, XLA, ONNX Runtime or similar runtimes


• Experience integrating custom hardware backends into PyTorch, ONNX or OpenXLA


• Knowledge of quantization and mixed-precision inference


• Experience with multi-device or distributed execution


• Background in AI accelerator or semiconductor environments

What Success Looks Like

• You enable reliable end-to-end execution of compiled models on our NPU


• Runtime overhead is minimal and performance targets are consistently met


• Memory management and scheduling are efficient and scalable


• The runtime architecture is robust, maintainable, and extensible


• Compiler, firmware, and hardware teams can build confidently on top of your execution layer


• The system supports real-world AI workloads with stability and observability

Join us in our mission to democratize AI compute - where your firmware expertise becomes the bedrock of tomorrow's AI breakthroughs.