Get your resume scored out of 100. Free ATS analysis.Rate yours
Google
Mountain View, California

Senior Software Engineer, AI/ML, Ads Training

Onsite$174,000 - $253,000/yrPosted today

We tailor your resume to this role and apply for you in seconds.

Apply to Senior Software Engineer, AI/ML, Ads Training at Google

Job details

Location
Mountain View, California
Work type
Onsite
Compensation
$174,000 - $253,000/yr
Posted
today
Apply on
careers.google.com

About this role

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience programming in Python or C++.
  • 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 Machine Learning infrastructure, ML execution frameworks (e.g., TensorFlow, JAX, PyTorch), or hardware accelerators (e.g., TPUs, GPUs).
  • Experience with large-scale distributed systems and performance debugging.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 5 years of experience with data structures and algorithms.
  • 1 year of experience in a technical leadership role.
  • 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 Ads Training Runtime team enables the core machine learning stack for the Ads Training Infrastructure. Our mission is to empower Ads machine learning teams with a flexible, high-performance infrastructure and intuitive tooling, enabling rapid innovation and seamless adoption of cutting-edge hardware and software technologies to maximize performance and deliver excellent business outcomes.

In this role, you will drive TPU efficiency at scale for our core training stack. You will lead vital efforts in model stability and hardware enablement, managing the technical challenges of migrating large-scale Ads models to JAX and supporting next-generation TPUs. By leading cross-stack optimizations, robust debugging infrastructure, and resource-efficient ML initiatives, you will directly deliver major efficiency wins, SWE cost savings, and business impact.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $253000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

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.
  • 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.
  • Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Ready to apply to Google?
We tailor your resume to this role and apply for you.

About Google

Google
Mountain View, California
WebsiteLinkedIn