Senior Software Engineer, AI/ML, Sensor Intelligence

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• Experience in working with sensors data and time series data.
  

Preferred qualifications:

• Master's degree or PhD in ML Time Series Data, Foundation Models or related technical field.
• Experience in machine learning, deep learning, and AI development, with a proven track record of building and deploying production-level models.
• Experience working in a research setting, collaborating with researchers and translating research findings into practical applications.
• Ability to work effectively with teams, including product managers, researchers, and other stakeholders, to drive AI adoption and integration.

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.

Sensor Intelligence (SI) team is building scalable AI solutions and foundation models that learn generalizable physiological representations from large-scale, real-world sensor data.

Join SI as the founding engineer in Bangalore. You have the opportunity to work on SOTA ML, be part of building sensor based foundation models, and collaborate with Google Research, Google DeepMind, and P&D teams worldwide.

With your technical expertise you will research on open ended problems on Sensor Intelligence, design, develop, test, deploy, maintain, and enhance AI/ML software solutions. You will also be expected to manage project priorities, deadlines, and deliverables.

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.

With your technical expertise you will research on open ended problems on Sensor Intelligence, design, develop, test, deploy, maintain, and enhance AI/ML software solutions. You will also be expected to manage project priorities, deadlines, and deliverables.

With your technical expertise you will research on open ended problems on Sensor Intelligence, design, develop, test, deploy, maintain, and enhance AI/ML software solutions. You will also be expected to manage project priorities, deadlines, and deliverables.

Responsibilities

• Write and test product or system development code. 
  
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  
• Evaluate large-scale, real-world sensor data for training sensor foundation model(s) and build new sensor foundation models.
• Collaborate with researchers and translating research findings from sensor data into practical applications for Fitness and health.