Senior Software Engineer, XR Embedded, Platforms and Devices

Google•Apply•Published 1 days ago•First seen 1 days ago

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.

For decades, the computing revolution has reshaped our world driven by breakthroughs in compute, connectivity, mobile, and now, AI. Google's XR team is at the forefront of the next major leap – the convergence of AI and XR. This is more than just new devices – it's about reimagining how we interact with the world around us. We're building a future where lightweight XR devices like smart glasses and headsets pair with helpful AI to augment human intelligence, offering personalized, conversational, and contextually aware experiences.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

Architect and develop embedded systems for intelligent edge sensing applications.
Develop firmware and drivers for embedded systems.
Collaborate with ML engineers to implement real-time ML sensing applications.
Optimize embedded ML model performance in terms of power, latency, and memory usage.
Create prototypes to demonstrate new edge sensing features.

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in C/C++.
Experience designing and architecting embedded systems including but not limited to MCUs, RTOS, memories, interfaces (e.g., I2C, SPI, UART, MIPI, CSI2, I3C, and BLE), and sensors (imaging and non-imaging).
Experience with firmware and driver developments for embedded systems.
Experience with low-power AI processor, sensor solutions, and overall system architecture.

Preferred qualifications:

Master's degree or PhD in Computer Science, or a related technical field.
5 years of experience with data structures and algorithms.
Experience in distributed machine learning, machine learning infrastructure, distributed systems, and machine Learning algorithms at scale.
Experience in training and optimizing deep learning models (e.g., convolutional neural networks, recurrent neural networks, or transformers).
Experience in C/C++, Python, and embedded software development for embedded systems.