Software Engineer, AI/ML Data and Training Infrastructure
Google · Mountain View, CA
- On site
- Full-time
- $252,000 / year
- Mountain View, CA
Job highlights
- Develop next-gen technologies for billions of users.
- Work on AI/ML data and training infrastructure.
- Solve complex engineering challenges at scale.
- Collaborate with diverse engineering teams.
- Influence global impact through Search.
About the role
Software Engineer AI/ML Data Training Infrastructure
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.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
About the job
Advance the platform to enable further ML use-case for discover feed recommendation. Design, implement, deploy, and maintain various projects. Take project ownership, including ideation, implementation, analysis, and maintenance. Learn and apply the technique to transform the product. Collaborate with peer team members (ranking, retrieval) for understanding various needs and system limitations in order to make informed decisions.
Minimum qualifications
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages, including Python and C++.
- 3 years of experience with ML Models and ML infrastructure (e.g., data processing, model optimization, evaluation, deployment).
- 2 years of experience with software design and architecture.
Preferred qualifications
- Experience iterating and managing projects.
- Experience collaborating with and supporting multiple client teams.
- Experience with large-scale distributed system design and research.
- Understanding of ML systems and generative AI technology.
Compensation
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.
Equal Opportunity Statement
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.
Key skills/competency
- Software Development
- Python
- C++
- Machine Learning (ML) Models
- ML Infrastructure
- Data Processing
- Model Optimization
- System Design
- Architecture
- Generative AI
Skills & topics
- Software Engineer
- AI
- Machine Learning
- ML Infrastructure
- Data Training
- Python
- C++
- Distributed Systems
- System Design
- Generative AI
- Tech
- Engineering
How to get hired
- Tailor your resume: Highlight your 5+ years in software development (Python, C++) and 3+ years in ML infrastructure.
- Showcase ML expertise: Emphasize experience with ML models, data processing, optimization, and deployment.
- Demonstrate system design skills: Include examples of large-scale distributed systems and software architecture.
- Research Google's values: Align your application with Google's commitment to innovation and user impact.
- Prepare for technical interviews: Be ready to discuss coding, algorithms, system design, and ML concepts.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key technical skills required for the Software Engineer AI/ML Data Training Infrastructure role at Google?
- For the Software Engineer AI/ML Data Training Infrastructure role at Google, key technical skills include strong proficiency in Python and C++, extensive experience with ML models and ML infrastructure (data processing, model optimization, evaluation, deployment), and a solid background in software design and architecture. Experience with large-scale distributed systems and generative AI technology is also highly preferred.
- What is the expected career growth for a Software Engineer at Google?
- Google offers significant career growth opportunities. As a Software Engineer AI/ML Data Training Infrastructure, you'll work on critical projects with chances to switch teams and projects as the business evolves. The company supports continuous learning and development, allowing you to take on new challenges across the full stack and advance your career within a fast-paced environment.
- How does Google approach diversity and inclusion in its hiring process for Software Engineers?
- Google is committed to equal employment opportunity and is a proud equal opportunity workplace and affirmative action employer. They do not discriminate based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. They also consider qualified applicants regardless of criminal histories.
- What is the typical interview process for a Software Engineer role at Google?
- The interview process for a Software Engineer role at Google typically involves several stages, including resume review, phone interviews, and on-site (or virtual on-site) interviews. These interviews focus on coding, algorithms, data structures, system design, and behavioral aspects. For AI/ML roles, expect questions specific to machine learning concepts and infrastructure.
- What kind of impact can a Software Engineer have at Google, specifically within the Search team?
- Software Engineers at Google, particularly within the Search team, have the opportunity to make a significant impact on billions of people globally. You'll be working on reimagining how people search for information by solving complex engineering challenges and expanding infrastructure, ensuring a universally accessible and useful experience.