Job Overview
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Job Description
Research Scientist at Google
Google Research is at the forefront of building the next generation of intelligent systems for all Google products. As a Research Scientist, you will contribute to groundbreaking projects by setting up large-scale tests, deploying promising ideas, and applying the latest theories to develop innovative products, processes, and technologies. You will work across various computer science domains, including machine learning, data mining, natural language processing, and core search, collaborating with skilled software developers and research scientists.
Responsibilities
- Author research papers to disseminate findings and create impact within Google and the broader research community.
- Contribute to research growth by sharing trends and best practices, reviewing academic papers, and serving on committees.
- Define data structures, frameworks, designs, and evaluation metrics for research solution development and implementation.
- Identify project timelines and secure necessary resources.
- Explore new research areas through collaboration with internal and external partners.
- Develop long-term research strategies to enhance the impact of Google's research initiatives.
- Identify and address complex technological gaps by engaging stakeholders and leaders.
About Google Research
Google Research maintains a diverse portfolio of projects, from fundamental research to new product innovation and infrastructure improvements. We provide our teams the freedom to focus on specific areas while ensuring alignment with organizational goals. You'll have the opportunity to work on real-world problems, prototyping implementations and designing new architectures.
Collaboration and Community
As a Research Scientist, you will actively contribute to the wider research community by sharing and publishing your findings. Ideas can stem from internal projects or collaborations with research programs at universities and technical institutes worldwide. Google Research teams work closely with other Google teams, maintaining the agility to adapt to evolving business needs.
Minimum Qualifications
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- 4 years of experience with research agendas across multiple teams or projects.
- One or more scientific publication submission(s) for conferences, journals, or public repositories.
Preferred Qualifications
- 2 years of experience in coding and leading multiple research efforts and influencing research direction.
Compensation
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Compensation is determined by role, level, and location. Your recruiter will provide specific salary range details for your preferred location during the hiring process. Compensation details listed reflect base salary only; bonus, equity, and benefits are additional.
Equal Opportunity
Google is an equal opportunity employer committed to diversity and inclusion. We consider all qualified applicants 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 with criminal histories, consistent with legal requirements. For accommodation, please complete our Accommodations for Applicants form.
Key skills/competency
- Research Scientist
- Machine Learning
- Deep Learning
- Data Mining
- Natural Language Processing
- Computer Science
- Algorithm Development
- Publication
- Research Strategy
- Prototyping
How to Get Hired at Google
- Tailor your resume: Highlight your PhD research, publications, and 4+ years of cross-team research experience. Emphasize coding skills and leadership if you have 2+ years of relevant experience.
- Showcase impact: Quantify your research contributions, especially publications, and experience in defining research strategy, frameworks, and evaluation metrics.
- Prepare for technical interviews: Brush up on core computer science, machine learning, deep learning, data mining, and NLP. Be ready to discuss your research agenda and problem-solving approach.
- Understand Google's research: Research current Google Research projects and publications to align your interests with their strategic goals.
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