Software Engineer III, Perception, XR
Google
San Jose, CA, US
Onsite
2026-06-21
Announced salary
$147k–$211k
Market rate in San Jose : $123K - $220K (median $171K) · BLS OEWS 2025
Job description
### **Minimum qualifications:**
* Bachelor’s degree or equivalent practical experience.
* 2 years of experience with software development in Python or Java/Kotlin.
* 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
* Experience in machine learning, audio processing and perception.
### **Preferred qualifications:**
* Master's degree or PhD in Computer Science or related technical fields.
* Experience working on establishing a scalable process for data and evaluation.
* Experience with data analytics, logging, or experiment frameworks.
* Experience communicating with client and platform teams.
**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.
Smart wearable glasses with AR and AI experiences strive to provide a natural voice\-based interaction, allowing users to effortlessly activate and engage with different applications like Gemini or translation. Our team focuses on leveraging the audio captured by multiple microphones on these devices and building on\-device deep lear
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