Machine Learning Systems Engineer (AI)

Location: Hybrid in Sunnyvale, California, or Toronto, Canada

Company

hirify.global Systems develops wafer-scale AI hardware and software for high-speed machine learning training and inference.

What you will do

• Design and implement runtime components and high-performance kernels for novel Core ML algorithms.
• Translate research prototypes into efficient hirify.global implementations and GPU reference comparisons.
• Profile and debug performance across ML frameworks, compilers, runtimes, communication layers, and kernels.
• Optimize computation, memory movement, communication, and concurrency for large-scale training and low-latency inference.
• Build benchmarks, instrumentation, automated tests, and numerical correctness validation.
• Collaborate with researchers and compiler, runtime, kernel, and inference engineers on end-to-end capabilities and platform improvements.

Requirements

• Bachelor’s, Master’s, PhD, or equivalent practical experience in computer science, computer engineering, electrical engineering, or a related field.
• Experience developing high-performance systems software, ML systems, runtimes, compilers, or computational kernels.
• Strong programming skills in C++ and Python.
• Understanding of parallel programming, memory management, concurrency, data structures, and performance optimization.
• Experience debugging and profiling complex software across multiple system layers.
• Familiarity with modern machine learning architectures and frameworks such as PyTorch or JAX.

Nice to have

• Experience with CUDA, Triton, low-level assembly, accelerator programming, or C-like domain-specific languages.
• Experience with compiler internals, distributed runtimes, custom hardware interfaces, or HPC systems.
• Knowledge of LLM training and inference, including attention, KV-cache management, parallel generation, or distributed execution.
• Contributions to open-source systems, ML frameworks, compilers, or kernel libraries.

Culture & Benefits

• Work on a wafer-scale AI platform designed beyond traditional GPU constraints.
• Opportunities to publish and open-source AI research.
• Access to one of the fastest AI supercomputers.
• Job stability combined with startup vitality and a non-corporate work culture.
• Commitment to an inclusive, diverse, and continuously learning workplace.