Google

Senior Software Engineer, AI/ML, Youtube Ads

Google$174K — $252K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree or equivalent practical experience
  • 5 years of software development experience in multiple programming languages
  • 3 years of experience in speech/audio technology, reinforcement learning, or ML infrastructure
  • 3 years in ML infrastructure including deployment and debugging
  • Experience in developing applications using Python and related libraries

Responsibilities

  • Write and test system development code
  • Collaborate on design and code reviews with peers
  • Contribute to and adapt documentation based on user feedback
  • Triage and debug product or system issues
  • Design and implement solutions in specialized ML areas

Benefits

  • Comprehensive healthcare plans
  • Retirement savings programs
  • Generous paid time off
  • Employee development opportunities
  • Flexible work arrangements
Full Job Description
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 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.
  • 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
  • Experience developing software applications using Python.
  • Experience using Python libraries and frameworks.

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
In this role, you will be a part of the YouTube Ads ML team, a research-focused product team that applies state-of-the-art machine learning techniques to deliver ad recommendations on YouTube by analyzing user activity sequence patterns to create valuable, high-quality, and personalized advertising experiences, fulfilling advertiser goals by identifying high-value users likely to purchase products and services, generating revenue to keep ad content free for users while supporting the creator ecosystem, and researching, designing, applying and launching innovative machine learning techniques.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.

The US base salary range for this full-time position is $174,000-$252,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. 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
  • 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.


About Google

Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
Learn more about Google
Size
156,500 employees
Market Cap
$1,115.4 billion
Industry
Net Income
$40.2 billion
Founded
1998
5 Year Trend
+23.3%
Revenue
$182.5 billion
NASDAQ

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