Senior Software Engineer, Ads, ML Infrastructure

19 Hours ago • 5-8 Years • Full Stack Development • $166,000 PA - $244,000 PA

Job Summary

Job Description

This Senior Software Engineer role at Google focuses on Ads and ML infrastructure. Responsibilities include writing and testing code, collaborating on design and code reviews, contributing to documentation, debugging system issues, and designing/implementing recommendation systems models. The ideal candidate will have extensive experience with ML infrastructure (model deployment, evaluation, optimization, data processing), building and deploying recommendation systems (retrieval, prediction, ranking, personalization), and software development in languages like Python or C++. The role requires strong architectural design skills and collaboration with stakeholders.
Must have:
  • 5+ years software development experience (Python, C++)
  • 3+ years ML infrastructure experience
  • 3+ years experience with recommendation systems
  • Strong software design & architecture skills
  • Experience with testing, maintaining, and launching software products
Good to have:
  • Master's/PhD in Computer Science
  • Technical leadership experience
  • Experience with accessible technologies
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages (e.g., Python, C++), and with data structures/algorithms.
  • 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 ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  • 3 years of experience building and deploying recommendation systems models (e.g., retrieval, prediction, ranking, personalization, search quality, embedding) in production.
  • Experience with building architecture.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or a related technical field.
  • 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 US base salary range for this full-time position is $166,000-$244,000 + 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

  • 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 recommendation systems models across different domains, leverage ML infrastructure, and contribute to architecture design.

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.

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