Augmented Reality Ai Jobs (NOW HIRING)

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in the C programming language.
• 3 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
• Experience in implementing image processing pipelines and managing concurrency for mobile features.

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• Experience developing and debugging software for Android, RTOS, or custom embedded platforms.
• Experience with optimizing systems with on-device computation units (e.g., GPU or NPU).
• Experience with peer-peer (P2P) networking over Bluetooth and Wi-Fi.
• Expertise in video and audio codecs (e.g., hardware or software).
• Experience with profiling tools including perfetto and pprof.

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.
XR team is responsible for the Android XR Platform, supporting Augmented Reality (AR) and Virtual Reality (VR) technologies that can see and sense the world from the same vantage point as you, and interweave digital information onto the world around you. Our goal is to give people superhuman capabilities by making computing more perceptive, immersive, and accessible through technologies like AI.
As a Senior Software Engineer, you join our XR Power and Performance team. You will be instrumental in developing, optimizing, and deploying the systems of our AR/VR glasses. This is a unique opportunity to work on problems at the intersection of connectivity stacks, video compression, and perception models.
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.
The US base salary range for this full-time position is $174,000-$252,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities

• Define metrics for a quality product in terms of good power and performance while preserving the core functionality of the product.
• Design and implement optimizations for saving power and/or ensuring a highly performant product.
• Contribute to the architecture and future roadmap of XR's products.
• Develop automation tools to trace measurements and regressions in an efficient way.

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