Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 2 years of experience building and deploying generative model applications, including techniques such as prompt engineering, prompt rewriting/tuning, and post-training evaluation.
- 2 years of experience with backend and server-side programming.
- Experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Preferred qualifications:- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience developing accessible technologies.
- Experience in developing user-facing products.
About the jobThe US base salary range for this full-time position is $147,000-$211,000 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 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.
- Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.
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