Senior AI/ML Performance Engineer

Requirements:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with AI and agentic tooling for development and research.

Preferred qualifications:

• Master's degree or PhD.
• 5 years of experience with data structures/algorithms in C++ and Python.
• Experience with an emphasis on algorithms, systems and tools for ML performance projections and evaluation.
• Experience designing or implementing components of a Deep Learning Compiler Stack (e.g., XLA, MLIR, TVM, ONNX Runtime).
• Experience in low-latency systems programming (e.g., C/C++) and optimizing data movement across the memory hierarchy (e.g., caches, HBM, I/O).
• Experience in performance engineering for ML/AI, including the design and optimization of GPU/TPU kernels, deep learning compilers, or low-latency systems infrastructure.

What you'll be doing:

• Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
• Build, maintain and validate HW/SW tooling to enable reliable and fast evaluation of options and solutions for ML/AI infrastructure (C++, Python).
• Build and maintain tools and methods to measure, visualize and analyse ML HW/SW performance.
• Define, implement and validate performance and cost metrics relevant for existing and future workloads and systems.
• Collaborate with other teams (hardware, compiler, ML research) to improve the end to end flow and results.

Perks and benefits:

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