Software Engineer, AI/ML, Computer Vision, XR

Google; San Jose (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google is seeking a Software Engineer to advance AI/ML in computer vision for XR. You will design and deploy depth estimation pipelines for Android XR headsets and smart glasses, optimizing for power efficiency and latency.

Responsibilities include end-to-end development, testing, and deployment, working with partner engineering teams, product, and UX to hit key KPIs. A Bachelor's degree and 2 years of ML infra experience are required, with C++ and Python proficiency.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with ML infrastructure (model deployment, model evaluation, data processing).
• Experience in designing computer vision systems.
• Experience with software engineering, C++, Python.

Responsibilities

• Architect, train, and implement machine learning models for depth estimation tailored for Android XR headsets and smart glasses.
• Design algorithms for split-compute architectures, optimizing specifically for extreme power efficiency and low latency.
• Lead the end-to-end development, testing, and deployment of a stable depth pipeline runtime for end users.
• Collaborate effectively with partner eng teams as well as with Product and UX to deliver on the main target KPIs.

Skills

ML infrastructure

Computer vision

C++

Python

Education

Bachelor's degree

Master's/PhD preferred

Tools

C++

Python

Job description

Software Engineer, AI/ML, Computer Vision, XR

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.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

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

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience in designing computer vision systems.
• Experience with software engineering, C++, Python.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• Experience in 3D reconstruction.
• Detailed understanding of mobile imaging systems (image sensors, optics, auto-exposure, image signal processor (ISP), etc.).

Responsibilities

• Architect, train, and implement machine learning models for depth estimation tailored for Android XR headsets and smart glasses.
• Design algorithms for split-compute architectures, optimizing specifically for extreme power efficiency and low latency.
• Lead the end-to-end development, testing, and deployment of a stable depth pipeline runtime for end users.
• Collaborate effectively with partner eng teams as well as with Product and UX to deliver on the main target key performance indicators (KPIs).

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