Research role focused on advancing the state-of-the-art in AI, particularly in reasoning, alignment, and memory. The role involves fundamental and exploratory research, developing learning algorithms, and contributing to the scientific understanding of intelligence and advanced machine intelligence.

Research Scientist role focused on Developmental AI (DevAI), aiming to build AI agents that learn autonomously from few samples of real-world data and interactions, similar to children. The role involves designing algorithms for robustness and sample efficiency, building datasets/simulators, and developing benchmarks. Emphasis on grounded language, communication, and multimodal modeling, with a goal of publishing groundbreaking papers and releasing open-source frameworks. The research intersects AI with the study of natural intelligence.

Research Scientist role focused on video generation and post-training of large-scale multimodal models within Meta's Fundamental AI Research (FAIR) team. The role involves developing generative models, optimizing post-training paradigms, and contributing to frontier models for next-generation AI systems, with a focus on video and media generation.

Research Engineer role at Meta's FAIR focused on advancing large language models, involving research, engineering, optimization, and deployment of both product and frontier models. Requires innovation, execution of research, experimental design, implementation, evaluation, and collaboration with cross-functional teams. Experience in building LLM systems at scale and publications in top-tier venues are essential.

Research Scientist role at Meta's FAIR team focusing on building world models from video for embodied and wearable agents, advancing research in self-supervised learning, predictive models, and model-based reinforcement learning. The role involves pushing the state of the art, publishing research, and developing efficient, scalable models.

Postdoctoral Researcher in Fundamental AI Research (FAIR) at Meta, focusing on cutting-edge research in AI/ML, deep learning, NLP, computer vision, and generative modeling, with a goal of understanding intelligence and achieving advanced machine intelligence. The role involves experimental design, code development, evaluations, publications, and contributing to Meta's product development.

Research Scientist at Meta Superintelligence Labs focused on foundational modeling and advancing the state of the art in speech and audio LLMs, including contextual ASR, TTS, and speech-to-speech capabilities. Requires a strong publication record and experience with post-training and evaluation of LLMs, including RL techniques.

Research Scientist role focused on advancing AI, specifically in vision models, 3D reconstruction, and generation, with the goal of building spatial and physically-aware AI for future human-computer interaction paradigms. The role involves conducting research, building and optimizing models, and working with large datasets.

Research Scientist at Meta's FAIR focusing on fundamental advancements in generative models and LLMs, including data efficiency and continual learning. The role involves research, engineering, and deployment for both product and frontier model efforts.

Research Scientist to contribute to Social Intelligence within complex multi-agent ecosystems, bridging centrally orchestrated multi-agent systems and social reasoning paradigms. Drive research focused on enabling autonomous agents to navigate the 'coordination bottleneck' through the development of Theory of Mind (ToM), intent modeling, and emergent social behaviors. Synthesize principles from reinforcement learning, game theory, and behavioral science to make agents capable of sophisticated alignment, ensuring ethical operation within human-centric environments.

Research Scientist role at Meta's FAIR in Paris focusing on fundamental research in generative models and LLMs, including data efficiency and continual learning. The role involves innovation, leading research, experimental design, implementation, evaluation, and publication.

Research Scientist at Meta's FAIR organization focusing on advancing LLM reasoning capabilities through reinforcement learning, synthetic data generation, and agentic techniques, with a specialization in formal and informal mathematical reasoning. The role involves leading research, contributing to experiments, publications, and open-sourcing efforts.

Research Scientist in FAIR focused on advancing AI science and developing technology towards superintelligence. The role involves developing joint audio-visual understanding systems, building and evaluating audiovisual language models for social interactions, and contributing to benchmarks. Requires a PhD and research experience in ML/AI, with a focus on computer vision, speech, and multimodal learning for embodied conversational agents.

Research Scientist focused on deep learning for memory in neural networks, applicable to personalization, lifelong learning, and large contexts. The role involves advancing state-of-the-art in architecture and memory, collaborating globally, and requires a PhD with publications in ML/DL, robotics, LLMs, or computer vision, and strong Python/C++ skills with PyTorch/TensorFlow.

AI Research Scientist focused on building the data foundation for Meta's advanced Large Language and Media Models. The role involves working with trillion-scale data, including organic and synthetic data generation, agent data, and frontier paradigms across pre-training, mid-training, and post-training stages. Expertise in multimodal data (image, video, agent) and collaboration with cross-functional teams are key.

AI Research Scientist focused on building the data foundation for Meta's advanced Large Language Models, contributing to data curation across pre-training, mid-training, and post-training stages, and exploring frontier paradigms for data at scale.

Research intern at Meta's FAIR focusing on fundamental AI research in language and multimodal foundations, aiming to make core algorithmic advances and apply them at scale. The role involves research in NLP, audio, speech, computer vision, ML, deep learning, and RL, with opportunities for publication.

AI Research Scientist focused on Vision-Language Models (VLMs) at Meta, pushing the state-of-the-art in multimodal reasoning and generation. The role involves long-term research, experimental execution, publication, and potential application to Meta's products. Requires a PhD and strong publication record in relevant AI conferences.

Research Scientist role focused on designing and building LLM-orchestrated multi-agent systems for autonomous materials discovery pipelines. This involves integrating agentic AI with computational tools, developing RAG systems, and collaborating with domain experts to accelerate discovery timelines. The role contributes to both production systems and published research.

Meta is seeking an AI Research Scientist to lead research and development of generative AI for video and multimodal understanding within their advertising pillar. The role focuses on creating foundation models for video generation, editing, audio generation, and visual search, with a strong emphasis on research publications and industry influence.

Meta's FAIR lab is seeking PhD candidates for 3-year fixed-term contracts to conduct fundamental AI research in areas like foundational models, LLMs, deep learning, computer vision, audio/speech, NLP, RL, and applied math. The work is expected to be open science and open source, with joint supervision from Meta and academic partners.

Research Engineer role focused on evaluating frontier AI systems and risks, developing and refining evaluations for multimodal and agentic models, and producing technical artifacts to inform risk assessments and launch decisions. Requires strong ML engineering and research skills, experience with agentic and multimodal models, and understanding of AI safety and threat models.

Research Engineer role focused on applying frontier AI, specifically LLMs and multimodal models, to Meta's social products. The role involves building and scaling post-training, evaluation, and serving systems, as well as developing an agentic platform. It emphasizes end-to-end ownership from research to production, impacting billions of users.

This role is for an AI Researcher focused on advancing the state-of-the-art in AI for chemistry and materials science, with a specific focus on modeling complex battery and electrolyte chemistries. The role involves fundamental and exploratory research, developing new datasets and models, and contributing to the understanding of intelligence and technology towards advanced machine intelligence. The researcher will publish their findings, open-source code, and enhance existing AI models for scientific applications.

Research Engineer role focused on advancing the field of AI by making fundamental advances in systems and infrastructure for large-scale machine learning, with a focus on enabling distributed training, resource efficiency, and hardware-software co-design. The role involves cutting-edge research, publishing results, and impacting Meta's product development.

Research Scientist role focused on full-stack robotics R&D, leveraging expertise in robot foundation models, tactile sensing, multimodal learning, and robotics systems. The role involves driving technical direction, defining strategy for scaling tactile data, and influencing foundation model development for robotics. Collaboration with robotics researchers, ML engineers, and scientists across the organization is key. Responsibilities include adapting/fine-tuning VLAs, developing scaled tactile/multimodal data strategies, training/fine-tuning foundation models, and representing the team externally.

Meta is seeking a Data Scientist for their Superintelligence Labs to lead the design, validation, and analysis of novel AI evaluations and benchmarks. This role focuses on scientific rigor, measuring frontier AI capabilities, and influencing research directions through data-driven insights and publications.

Research Scientist role focused on designing and developing novel benchmarks and evaluation methodologies for frontier AI capabilities within Meta Superintelligence Labs (MSL). The role involves measuring and understanding AI capabilities, influencing research direction, and collaborating with researchers and technical leadership. Requires a strong publication record and experience in machine learning research, particularly in evaluation and deep learning.

Research Scientist role focused on developing and implementing novel evaluations for frontier AI systems, shaping research direction and model development. Requires strong ML research background, experience with LLM/multimodal evaluation, and publication record.

Research Engineer role focused on building and curating benchmarks and evaluation environments for advanced AI models across text, vision, and audio. The role involves developing novel benchmarks, integrating existing ones, and creating scalable evaluation tooling to directly impact research direction and model development. Requires strong ML engineering and research skills, Python proficiency, experience with ML frameworks, and a track record of publications in relevant venues.

AI Research Scientist focused on advancing AI/ML for Monetization Ranking, developing large-scale models, sequence learning, generative models, graph-aware LLMs, AutoML, RL techniques (including RLHF), and causal learning. The role involves optimizing ML systems with hardware-software co-design and various data-related techniques like semi/self-supervised learning and continual learning.

Research Engineer focused on Monetization AI, developing and implementing large-scale model architectures, generative modeling, and ML pipelines for recommender systems. Emphasizes training scalability, signal scaling, and responsible AI practices, with a requirement for publications at top AI conferences.

Research Engineer focused on AI safety for large language and multimodal models, involving designing, implementing, and evaluating safety techniques, curating datasets, fine-tuning models, and building scalable infrastructure for safety evaluation and mitigation. Requires experience with LLM training, fine-tuning, evaluation, and safety research, along with Python and PyTorch.

AI Research Scientist focused on safety alignment for large language models and multimodal AI systems. Responsibilities include designing, implementing, and evaluating novel safety techniques, curating datasets, fine-tuning LLMs for safety policies, and building infrastructure for evaluation and mitigation. Requires a PhD, 3+ years of research experience, publication record, Python/PyTorch proficiency, and experience with RL techniques for LLM fine-tuning.

AI Research Scientist focused on building the data foundation for Meta's advanced Large Language and Media Models. The role involves data curation across pre-training, mid-training, and post-training stages, handling trillion-scale data challenges including organic and synthetic data generation, and contributing to frontier paradigms. Collaboration with cross-functional teams and leading complex technical projects are key.

Research Engineer role focused on building data foundations for Meta's advanced LLMs and LMMs, contributing to data curation across pre-training, mid-training, and post-training stages for various modalities. The role involves architecting scalable data systems, generating synthetic data, and working with trillion-scale datasets.

Meta is seeking AI research engineers to build the data foundation for their advanced LLMs. The role involves working with large-scale data across pre-training, mid-training, and post-training stages, focusing on areas like organic data curation, synthetic data generation, agent data, and frontier paradigms. This position is within Meta Superintelligence Labs (MSL) within FAIR, contributing to models like Llama.

Meta is seeking an AI Research Scientist specializing in Robotics to push the frontiers of embodied AI. This role involves inventing and improving data-driven paradigms for robots using various modalities, developing ML/NN algorithms, and building/benchmarking new functionality. The position requires a PhD, extensive experience in robotics research areas, and a proven track record of significant results via publications and patents.

Research Scientist Intern PhD, Applied Research at Meta, focusing on developing novel state-of-the-art generative AI algorithms and systems, advancing intelligent machine science, and applying research at scale. Requires a PhD in a relevant technical field and experience in machine learning, deep learning, computer vision, and/or NLP.

Research Scientist Manager to lead a team focused on measurement and evaluation of AI Assistants powered by foundation models. The role involves defining scientific strategy for evaluation, ensuring methodological rigor, and collaborating with product, engineering, and training teams to ensure reliability and trustworthiness at scale.

Meta is seeking Research Scientist Interns to join the Products and Applied Research team, focusing on advancing generative AI through fundamental research in understanding and interacting with the world. The role involves research in generative AI, deep learning, computer vision, and NLP, with opportunities to make core algorithmic advances and apply ideas at scale, publishing research results for product development.

AI Research Scientist focused on advancing recommender systems by modeling user and ad interactions as generative sequence modeling problems, moving beyond traditional classification methods. The role involves research, algorithmic innovation, and productionizing breakthroughs for Meta's monetization pillar, with a focus on large language models (LLMs) and artificial general intelligence (AGI).

Research Scientist Intern focused on AI Alignment, developing novel algorithms and systems in deep learning, ML, and AI. The role involves conducting state-of-the-art research, collaborating with researchers, and publishing findings, with opportunities to apply research to Meta products. Requires a Ph.D. in a relevant field and experience with Python/C++ and deep learning frameworks.

Meta is seeking a PhD Research Scientist Intern to advance AI research in areas like deep learning, NLP, speech, and computer vision, with a focus on Large Language Models and multimodal inputs. The intern will perform research, develop algorithms, analyze systems, and collaborate on projects with the potential for product application, aiming to publish research findings.

Research Scientist Intern at Meta focused on photorealistic telepresence and autonomous social agents in AR/VR. The role involves generative AI for image/video synthesis, digital human motion, social signal encoding, face/body reconstruction, and multimodal LLMs (speech-to-speech, audio-visual). Requires PhD in a related field, ML experience, deep learning frameworks, Python, and a track record of publications/patents.

Research Scientist Intern focused on developing ML-powered robotic control policies for manipulation and teleoperation, involving data collection, training models (RL, IL, LBMs), and benchmarking algorithms.

Research Scientist focused on embodied AI and robotics, developing novel data-driven paradigms and algorithms using machine learning and neural networks for both simulated and real-world robots. The role involves pushing the frontiers of AI in robotics, from low-level control to high-level intelligence, and requires experience with various modalities and research areas like reinforcement learning, vision, and LLMs.

Meta's Monetization Ranking AI Research team is seeking motivated AI specialists to drive SOTA research in AI/ML for personalized ads, focusing on ranking, retrieval, model architecture, and optimization. The role involves developing and implementing large-scale model architectures, sequence learning, generative modeling, graph-aware LLMs, AutoML, and RL techniques. Qualifications include a Bachelor's degree, 2+ years of research experience, Python proficiency, and first-author publications at top AI conferences. Experience taking ideas from research to production and implementing responsible AI practices is also required.