Software Engineer III, AI​/ML, DSP​/HTP Optimisation

Software Engineer III, AI/ML, DSP/HTP Optimisation

Requirements:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in C++ or Python programming languages, or 1 year of experience with an advanced degree.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).

• Master's degree or PhD in Computer Science or related technical fields.
• Deep understanding of machine learning principles to ensure algorithms perform within strict power limits.
• Maintaining a current and thorough understanding of the latest developments in Digital Signal Processors (DSP), Hexagon Tensor Processors (HTP), and system‑on‑chip (SoC) architectures to effectively leverage hardware‑specific features for maximum efficiency and thermal management.

Google's software engineers develop the next‑generation technologies that change how billions of users connect, explore, and interact with information. In this role, you will conduct rigorous power profiling and implement hardware‑specific optimizations to ensure feature performance remains consistent across all use cases. You will work at the intersection of ML and system architecture and define efficiency standards on next‑generation hardware. You will optimize the end‑to‑end performance of ML models to meet strict power and thermal constraints by leveraging specialized expertise in Hexagon Tensor Processors (HTP) and Digital Signal Processors (DSP) architectures.

• Utilise Digital Signal Processors (DSP) and Hexagon Tensor Processors (HTP) architectures to accelerate ML models while effectively minimizing thermal impact.
• Conduct rigorous power profiling and implement hardware‑specific optimizations to maintain consistent feature performance across all use cases.
• Own the end‑to‑end performance optimization of models to operate within a strict power budget.
• Define the efficiency standards on next‑generation hardware at the intersection of ML and system architecture.