Research Scientist, Google Research GenAI Experiences

Minimum Qualifications

PhD degree in Computer Science or related field; experience in computer vision, machine learning, or natural language processing; proficiency in Python; and scientific publications (e.g., CVPR, ICCV, NeurIPS, ICML, ICLR).

Preferred Qualifications

2 years coding experience; 1 year of research agenda ownership; experience with JAX/PyTorch, Python; building and launching ML models (including LLMs and NLP); quantitative research for data analysis; familiarity with Google infrastructure such as Flume.

About The Job

As a Research Scientist at Google Research GenAI Experiences, you will design, implement, and evaluate advanced ML models on large-scale datasets, deploy promising ideas quickly, and manage deadlines and deliverables. You will build experiments, prototype implementations, and create new architectures addressing areas such as machine learning, data mining, natural language processing, hardware and software performance analysis, and compilers for mobile platforms. You will also contribute to the research community by publishing and sharing findings from internal projects and collaborations with global research programs.

Responsibilities

• Design, implement, and evaluate advanced ML models using large datasets.
• Architect and maintain systems for model training and serving.
• Perform statistical analyses on data to derive actionable insights.
• Publish original research and contribute novel methodologies.
• Collaborate with partners to integrate ML models into products.

Compensation & Benefits

The US base salary range for this full-time position is $141,000-$202,000 plus bonus, equity, and benefits. Compensation is determined by role, level, location, and additional factors.

Equal Opportunity

Google is an equal opportunity workplace and affirmative action employer. Applicants with disabilities requiring accommodations should complete the Accommodations for Applicants form.

Key skills/competency

• Computer Science
• Machine Learning
• Python
• Research
• Data Analysis
• Software Development
• Statistical Analysis
• ML Models
• Publication
• Collaboration