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.

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.

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.

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.

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.

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.

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.

Meta's Monetization Ranking AI Research team is seeking AI Research Scientists to advance AI/ML for personalized ads, focusing on ranking, retrieval, model architecture, and optimization. The role involves developing and implementing large-scale models, generative solutions, RL techniques, and causal learning, with a strong emphasis on research and publications in top-tier AI conferences, and taking ideas from research to production.

Research Scientist at Meta focused on developing and implementing novel quantitative and machine learning methods to answer product questions and generate insights. The role involves working with large datasets, applying advanced ML techniques like Bayesian modeling, reinforcement learning, and causal inference, and optimizing neural network models. The scientist will also draft software from scratch to implement these methods and collaborate with cross-functional teams.

Meta is seeking a PhD intern to work on machine learning systems and models for their Core Ads Growth team. The intern will develop scalable classifiers and tools, adapt ML methods for parallel environments, and contribute to building ML systems for Meta's products. The role involves research and development in areas like deep learning, NLP, recommendation systems, and computer vision.

Research Scientist Intern role focused on audio and hearing science, involving the design and analysis of audiologic experiments, development of novel algorithms for speech enhancement and hearing assistance, and collaboration with researchers. Requires a PhD in a related field and experience in experimental design, programming, and signal processing.

Research Scientist at Meta focused on developing and implementing optimization algorithms, large-scale distributed systems, and machine learning models for various platforms. The role involves data analysis, system engineering, and creating tools for data migration and product development.