דרושים » אלגוריתמים » AI Research Scientist, VLLM (vision large language models) - Generative AI

Meta is seeking AI Research Scientists to join fundamental and applied research teams, which are focused on making significant progress in AI. Advances in AI are key to our mission, spanning some of the most pressing research challenges of our generation across such areas as artificial intelligence, machine learning, computational statistics, and applied mathematics, particularly including areas such as deep learning, generative models, reinforcement learning, computer perception, natural language processing and speech. The ideal candidate will have a keen interest in producing new science to understand intelligence and technology to make computers more intelligent, or to work on more applied problems across the company.
Research Scientist, Generative Models (PhD) Responsibilities
Collaborate on research projects within a globally based team to advance the science and technology of intelligent machines.
Collaborate on research that enables learning the semantics of data (images, video, text, audio, speech and other modalities).
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Drive team goals & technical direction to pursue opportunities that make your larger organization more efficient.
Influence progress of relevant research communities by producing publications.
Contribute research that can be applied to Meta product development.
Devise better data-driven models of human behavior.

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.

Meta is seeking Research Interns to join our Generative AI research efforts across modalities (images, video, 3D, audio, etc.). We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as generative modeling, deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Generative AI (PhD) Responsibilities
Develop novel state-of-the-art generative AI algorithms and corresponding systems, leveraging various deep learning techniques.
Perform research to advance the science and technology of intelligent machines.
Perform research that enables learning the semantics of and training generative models of data (images, video, 3D, text, audio, and other modalities).
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Disseminate research results.

We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.

Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Large Language Models (PhD) Responsibilities
Perform research to advance the science and technology of intelligent machines.
Develop novel and accurate Code Generation, World Modeling, NLP, and systems, leveraging Deep Learning and Machine Learning on big data resources.
Analyze and improve efficiency, scalability, and stability of various deployed systems.
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Publish research results and contribute to research that can be applied to Meta product development.

We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, signal processing, information retrieval, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, AI Core Machine Learning (PhD) Responsibilities
Develop novel state-of-the-art machine learning algorithms and corresponding systems, leveraging various deep learning techniques.
Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence.
Devise better data-driven models for information retrieval, Multi-modal fusion, generation or media understanding (CV, NLP, Speech/ Audio).
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Publish research results and contribute to research that can be applied to Meta product development.

Central Applied Science (CAS) is a research and development team, working to improve Metas products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the Meta family of apps. The work we do enhances the Meta family of apps that enable billions of people to communicate with each other daily.

Central Applied Science is interdisciplinary, with expertise in computer science, statistics, machine learning, and economics among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at Meta and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise.

We are looking for research interns to join the Product Algorithms team in Central Applied Science. The team is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally increase the magnitude of Metas successes. The ideal candidate will have extensive graduate training in computer science, machine learning, or related disciplines, and the passion to solve real world hard scientific problems. By applying your expertise and passion you will be empowered to drive impact across a range of products, infrastructure and operational use cases at Meta.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Central Applied Science (PhD) Responsibilities
Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products.
Develop novel quantitative methods on top of Meta's unparalleled data infrastructure.
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Communicate best practices in quantitative analysis to partners.
Work both independently and collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value.

As 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.

In this role, you will be working on improving the factuality of Google's large language models that power prominent google products such as search AI overviews, gemini chat, cloud and YouTube.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

Responsibilities
Perform research for improving large language model (LLM) factuality and it's grounding capabilities.
Collaborate with other research teams to improve large language model (LLM) factuality.
Integrate innovative research into google products by collaborating with product teams.

As 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.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, were 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.

Responsibilities
Drive project work by defining the data structure, framework, design, and evaluation metrics for research solution development and implementation. Identify timelines and obtain resources needed.
Identify defined problems/gaps in existing technology and engage stakeholders and leaders to address them.
Lead the research of technology for improving Large Language Model (LLM) efficiency of performing target capabilities or supporting many capabilities, such as novel architectures and improved pre-training.
Collaborate with other Research teams to expand efficient LLM technology.
Collaborate with Google first-party partner teams to deliver new technologies to production.

As 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 developing advanced methodologies tailored specifically for multilingual environments. We focus on pre-training multilingual models, enhancing the quality of multilingual instruction-tuning datasets, refining multilingual evaluation processes, boosting knowledge transfer across languages, and optimizing multilingual tokenization among other initiatives.

The Technology & Society organization connects research, people, and ideas across Google and Alphabet to help shape and advance our most ambitious technology innovations and initiatives and their impact on users and society for the better, and responsibly. In addition, we also aim to share perspectives, engage, and collaborate with others externally on technology related issues and opportunities for society.

Responsibilities
Author research papers to share and generate impact of research results across the team and in the research community.
Research and develop technology for improving multilingual Large Language Models (LLM) such as instruction-tuning, pre-training, multilingual reasoning.
Research and develop technology for pre-training LLMs for languages other than English.
Collaborate with other research teams to expand multilingual LLM technology.
Collaborate with Google first-party partner teams to deliver new multilingual technologies to production.

As 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 focuses on developing foundation models for remote sensing (i.e., satellite, aerial) imagery. We aim to simplify and enhance various remote sensing tasks including land use/land cover segmentation, object detection, and change detection for use by Google teams and external partners. We also investigate natural language interfaces for remote sensing imagery through vision-language models and tasks such as captioning and visual question answering.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

Responsibilities
Explore research directions, generate hypotheses and perform rigorous experimentation in several sub-domains (e.g., pre-training recipes, multi-modality, temporal sequences).
Contribute to shaping the team's roadmap, help prioritize research directions, with focus on innovation and usability.
Work with other researchers across Google to connect multiple geospatial efforts.
Help teams use foundation models and optimize its use on their tasks.
Advise and mentor team members.

As 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.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

Responsibilities
Lead research and develop technology for evaluating the consistency, grounding and attribution of generative Large Language Model (LLM) outputs, as well as technology for improving factuality at pretraining, including augmented generation.
Collaborate with other research teams to expand output verification technology.
Collaborate with Google first-party partner teams to deliver new technology to production.
Drive academic-quality research that would result in conference publications