Staff Software Engineer, AI/ML
Job Summary
Job Description
- 8+ years software development experience
- 5+ years testing and launching software
- 3+ years software design and architecture
- 1+ year experience with ML, AI, and scalable platform development
- Design, develop, test, deploy, maintain software
- Master's/PhD in Engineering or Computer Science
- Experience with NLP and Generative AI
5 skills required
Job Details
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
- 1 year of experience with machine learning, AI, and scalable platform development.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience in building products using Machine Learning techniques including Natural Language Processing (NLP).
- Experience with Generative AI.
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
The Enterprise Knowledge and Moma team develops and maintains platforms that empower Corp Eng to create outstanding AI-powered knowledge discovery experiences within Google.
We are building AI capabilities and agentic search experiences to enhance Googlers' productivity and efficiency. Our approach leverages the best of Google's internal tools and external technologies to provide engineering teams with the means to rapidly and effectively deliver solutions.
The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
The US base salary range for this full-time position is $197,000-$291,000 + 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
- Design, develop, test, deploy, maintain, and enhance large scale software solutions.
- Shape the future by defining and driving the technical vision for AI-powered experiences for Googlers.
- Balance the creation of tailored, short-term end-to-end prototypes with the long-term goal of developing scalable, generalized AI-first solutions.
- Participate in and lead architecture and engineering discussions with colleagues and stakeholders, applying sound technical judgment to guide decisions.
- Review code and design documentation, proactively addressing roadblocks for team members, and providing constructive feedback to promote adherence to best practices.
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