Senior Machine Learning Software Engineer, GPU Acceleration, Silicon
1 day ago
Minimum qualifications:
- Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience.
- 5 years of experience in software engineering with performance-critical systems or low-level development.
- Experience with on-device machine learning.
- Experience with programming in C and C++.
- Experience with GPU programming (e.g., CUDA, OpenCL, Metal, Vulkan Compute).
- Experience in designing, implementing, and optimizing machine learning models using frameworks like TensorFlow or PyTorch.
- Experience with performance analysis, profiling, and debugging tools for mobile devices.
- Knowledge of computer architecture with mobile systems on a chip (SoC) architectures and GPU pipelines.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
The Silicon team develops silicon solutions that provide differentiated user experiences in Google Hardware products and optimize performance and power for specific use cases. This includes systems on a chip (SoCs) and related signal, reasoning, and sensor integrated circuits (ICs) for the product portfolio.
In this role, you will partner with cross-functional teams to deliver software to enable a quality user experience on Pixel and other hardware products.
Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.
Responsibilities
- Design and implement optimized GPU kernels for compute-intensive workloads.
- Enhance machine learning model inference performance on mobile Graphics Processing Unit (GPU) architectures.
- Implement novel machine learning-based algorithms to advance GPU graphics rendering capabilities.
- Conduct system-level performance analysis, identify bottlenecks, and implement optimizations across the hardware/software stack.
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