Ai Brainer
Research Scientist, AI for Science
Ai Brainer, Mountain View, California, us, 94039
The role involves contributing to cutting-edge research in artificial intelligence and machine learning, particularly in the fields of computational chemistry and material science. Research Scientists collaborate with hardware and software engineers to devise experiments, prototype implementations, and design new algorithms for real-world applications. They are tasked with integrating the latest research into practical projects, determining the scope of problems, and providing insights on data requirements. In this capacity, they serve as a bridge to the broader research community and other teams within the organization.
Required Qualifications and Skills
A PhD in Computer Science or a related technical field is required, along with five years of experience in areas such as computer vision, machine learning, and optimization. At least two years of experience applying these techniques in chemistry and materials science is necessary. Candidates should have experience with programming languages, particularly Python and C++. Additionally, research contributions, including published papers in machine learning venues, are expected. Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information. At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google’s users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google’s product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.
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A PhD in Computer Science or a related technical field is required, along with five years of experience in areas such as computer vision, machine learning, and optimization. At least two years of experience applying these techniques in chemistry and materials science is necessary. Candidates should have experience with programming languages, particularly Python and C++. Additionally, research contributions, including published papers in machine learning venues, are expected. Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information. At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google’s users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google’s product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.
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