Qualifications

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing or other ML discipline.
  
• Experience in Generative AI (e.g., Large Language Models, Multi-Modal, Large Vision Models).
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects.
• 3 years of direct experience developing and launching ML based product workflows.
  
• 3 years of experience with standard Google ML Infrastructure and frameworks, and willingness to learn new ones as necessary.
  
• Experience developing/using Machine Learning models for Vision.
  
• Experience with on-device ML models.

Summary

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing or other ML discipline.
  
• Experience in Generative AI (e.g., Large Language Models, Multi-Modal, Large Vision Models).
  

Description

As a Machine Learning Software Engineer, you will help make multimodal video first AI experiences a reality.You will make direct technical contributions while navigating ambiguity. This role will be largely self-directed and operate independently with minimal oversight. We value those who are willing to help out with whatever moves the project forward.

We work closely with many teams across Google, including Astra, Gemini Nano, Gemini Live, and SIlicon. Our work engages several layers of the stack, including modeling, efficiency on silicon, and user experiences/interaction paradigms.
This is a unique chance to join our multidisciplinary team working on AI research, building from zero to one. You will be working directly with advanced AI technologies and turning new ideas into finished products, fundamentally impacting people’s lives.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

The US base salary range for this full-time position is $189,000-$284,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• Build emerging, edge focused multimodal (e.g., image and video) AI capabilities partnering closely with Researchers across Alphabet (e.g., Google Research, Google DeepMind).
  
• Ideate and run experiments to enhance model quality and latency for on-device models.
  
• Partner closely with Product teams across Partners and Devices (e.g., Android, Pixel, Gemini/Bard, AR, etc.) to develop novel user experiences.
  
• Collaborate closely with cross-functional and cross-product area partners to plan and prioritize projects.
  
• Design, develop, and launch new product features.