Software Engineer III, AI/ML

4 Months ago • 3-5 Years • Artificial Intelligence

Job Summary

Job Description

Google is seeking a Software Engineer III, AI/ML in Bengaluru, India. This role involves developing and optimizing AI/ML models, collaborating on design and code reviews, contributing to documentation, and troubleshooting system issues. Responsibilities include writing product/system code, ensuring best practices, adapting content based on user feedback, and implementing solutions in specialized ML areas. The ideal candidate will have experience with software development, data structures, algorithms, ML infrastructure (model deployment, evaluation, optimization, data processing), and one or more specialized ML fields (e.g., speech/audio, reinforcement learning).
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software development experience
  • 2+ years experience with data structures/algorithms
  • 1+ year experience with ML infrastructure
  • 1+ year experience in a specialized ML area (speech/audio, reinforcement learning, etc.)
  • Code writing, debugging, and collaboration skills
Good to have:
  • Master's or PhD in CS or related field
  • Experience with accessible technologies

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  • 2 years of experience with data structures or algorithms.
  • 1 year 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.
  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience developing accessible technologies.

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.

The Platforms and Ecosystems product area encompasses Google's various computing software platforms across environments (desktop, mobile, applications). The products provide enterprises, and ultimately end users, the ability to utilize and manage their services at scale. We build innovative and compelling software products—from apps to TVs, from laptops to phones—that have an impact on people’s lives across the world.

Responsibilities

  • Write 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.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

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