Software Engineer, GeminiApp

Snapshot

Our team is responsible for speech experience inside GeminiApp, handling activation, ASR and TTS quality, speech personalization, interruptions, and conversation termination. Our team includes software engineers that build and maintain the backend infrastructure for these aspects of the product.

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we are working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

In this role, you will:

• Deploy models that classify GeminiApp data, ensuring that the models' inputs are passed properly within the server and from mobile devices, and ensuring its outputs are used effectively


• Build monitoring dashboards and alerting systems to ensure that these models continue to operate as designed


• Update infrastructure to ensure that data handling adheres to company privacy policy standards


• Perform and assist with data analysis to identify quality, latency, and reliability issues through live experiments, and identify opportunities for future improvement


• Participate in planning and implementing improvements, and collaborating with other team members on other GeminiApp speech experience systems.

About you

You are a talented and resourceful engineer, with a background in complicated Google infrastructure like GeminiApp and Assistant. You can quickly get familiar with a new codebase, and know how to leverage LLMs to work quickly. You thrive on seeing your work deployed to millions of users, and care about the end-user experience. You work well independently and collaboratively, and demonstrate good judgement balancing short- and long-term needs. You come up with ideas on your own, enjoy discussing them, and work hard to make sure that the best ideas succeed, regardless of where they came from. You are good at communicating clearly, and good at ramping up quickly, and at mentoring others.

In order to set you up for success as a Machine Learning Software Engineer at Google DeepMind, we look for the following skills and experience:

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  • BS, MS or PhD degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry
  
  
  • Experience working on software engineering projects from proof-of-concept through to implementation.
  
  
  • Proven knowledge and experience of Python, C++, GCL, SQL in production environments
  
  
  • Experience in applying experimental ideas to applied problems
  
  
  • Knowledge of machine learning and statistics, including modern techniques like prompt optimization
  
  
  • Experience productionizing state-of-the-art small classification and large language a plus
  
  

The US base salary range for this full-time position is between $197,000 - $291,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.