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.
As a Machine Learning Engineer with a focus on 3D geometry, you will be responsible for the entire model life cycle from data generation to model optimization. You will bridge the gap between advanced research in monocular depth modeling and the real-world requirements for robustness in video and user interface environments.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.
Responsibilities
- Manage the end-to-end training process for high-impact machine learning models.
- Develop and optimize models capable of running efficiently on both consumer devices and server-side infrastructure.
- Own the robustness and data quality of depth models to resolve critical stability and user experience challenges.
- Adapt research in monocular depth modeling to ensure reliable performance across real-world scenarios.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in Python or C++ programming languages, or 1 year of experience with an advanced degree.
- 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Experience developing accessible technologies.
- Experience in Machine Learning methods with a strong background in 3D geometry.
- Proficiency in building and deploying models for both on-device and server environments.
- Demonstrated ability to independently handle data generation, model training, and optimization pipelines.