Software Engineer III, AI/ML, YouTube Ads

1 Month ago • 3-5 Years • Artificial Intelligence • $141,000 PA - $202,000 PA

Job Summary

Job Description

This Software Engineer III position at YouTube Ads focuses on building machine learning systems using massive datasets (billions of YouTube queries). Responsibilities include developing sophisticated user modeling and ad features, researching novel model architectures, and deploying models using TensorFlow and TPUs. The role requires expertise in recommendation systems, ads, and machine learning infrastructure. Candidates should possess strong skills in C++, Python, data structures, algorithms, and experience with at least one area of machine learning specialization such as speech/audio processing, reinforcement learning, or ML infrastructure. The successful candidate will collaborate with experienced leadership to build expertise in cutting-edge machine learning techniques.
Must have:
  • C++ and Python experience
  • Data structures and algorithms expertise
  • ML infrastructure experience (deployment, evaluation)
  • Experience with at least one ML specialization (e.g., speech/audio, reinforcement learning)
  • Building ML systems on large datasets
Good to have:
  • Master's/PhD in CS or related field
  • Experience with accessible technologies
  • Scaling ML systems and large language models
  • Experience with ads clicks/conversions prediction
  • Experience with recommendation systems
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in C++ and Python, 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), Machine Learning infrastructure, or specialization in another Machine Learning field.
  • 1 year of experience with Machine Learning infrastructure (e.g., model deployment, model evaluation, data processing, debugging).

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience developing accessible technologies.
  • Experience in Scaling machine learning systems and Large language models Generative models.
  • Experience in Ads business Clicks and conversions prediction, in an ads or non-ads context Recommendations systems.

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 US base salary range for this full-time position is $141,000-$202,000 + 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 .

Responsibilities

  • Build machine learning systems on data (billions of YouTube queries).
  • Build expertise on SOTA Machine Learning techniques for recommendation systems, ads and product landscape by working with experienced execuitve leads.
  • Design and build features Sophisticated user modeling, Ad features, Video features.
  • Research novel model architectures, read papers, implement and deploy them.
  • Work with the Machine Learning techniques, tools like TensorFlow, Adbrain, Tensor Processing Unit.

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