Minimum qualifications:- Bachelor's degree in Computer Science, Mathematics, Applied Stats, Machine Learning, a related field, or equivalent practical experience.
- 5 years of experience with inference-optimized model design.
- Experience working with product teams.
Preferred qualifications:- Experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models.
- Experience with fine-tuning large models (e.g., supervised, RLHF).
Responsibilities - Focus on inference-optimized model design for Gemini pretraining.
- Understand common Accelerated Linear Algebra (XLA) primitives and how JAX code runs on TPUs in practice.
- Work across the Large Language Model (LLM) preparation stack (e.g., pretraining, fine tuning, serving) to deliver strong models.
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 .
