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Sydney, Österreich Google Inc. VollzeitStaff Research Scientist, Machine Learning Efficiencycorporate_fare Google place Sydney NSW, AustraliaApplyinfo_outlineX Info At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google's technology, platforms and people. We welcome Indigenous...
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Sydney, Österreich Google Inc. VollzeitStaff Research Scientist, Machine Learning Efficiencycorporate_fare Google place Sydney NSW, AustraliaApplyinfo_outline X Info At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google's technology, platforms and people. We welcome Indigenous...
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Sydney, Österreich Google Inc. VollzeitStaff Research Scientist, Machine Learning Efficiencycorporate_fare Google place Sydney NSW, AustraliaApplyinfo_outline info_outline X Info At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google's technology, platforms and people and we...
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Sydney, Österreich Google Inc. VollzeitStaff Research Scientist, Machine Learning Efficiencycorporate_fare Google place Sydney NSW, AustraliaApplyinfo_outlineinfo_outline X Info At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google's technology, platforms and people and we...
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Sydney, Österreich Tideri Jobbörse VollzeitStaff Research Scientist, Machine Learning Efficiency corporate_fare Google place Sydney NSW, Australia Apply info_outline X Info At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google's technology, platforms and people.We welcome...
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Staff Research Scientist, Machine Learning Efficiency
vor 2 Monaten
Staff Research Scientist, Machine Learning Efficiencycorporate_fare Google place Sydney NSW, Australia
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About the jobAs an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
Our team is committed to advancing in the areas of efficient architectures, training efficiency of foundational models, data efficiency, and inference efficiency.
In this role, you will have opportunities to collaborate with Google teams over the world and advance in the above mentioned areas, enable fundamental breakthroughs, and pioneer next-generation products.
Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we're working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.
Minimum Qualifications:PhD in Computer Science, a related technical field, or equivalent practical experience.4 years of experience with research agendas across multiple teams or projects in Machine Learning (ML), ML Efficiency, ML Optimization, or a related field.Experience with programming languages (e.g., Python or C/C++).One or more scientific publication submissions for conferences, journals, or public repositories (e.g., ICML, ICLR, NeurIPS).Preferred qualifications:Experience in innovative research.Experience as a leader within a research team.Responsibilities:Develop fundamental advances in algorithms and foundational model architectures that improve the speed of training and generalization of deep learning models.Develop fundamental advances to make inference with foundational models more efficient and flexible including knowledge adoption and distillation techniques.Work on data subset selection and more efficient ways to train with large data sets.Improve the entire model deployment pipeline including formulations for pre-training, instruction and tuning, and Reinforcement Learning from Human Feedback (RLHF).Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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