ByteDance

Research Scientist focused on pioneering AGI through large-scale multimodal foundation models, integrating video, audio, and language with a focus on visual latent reasoning and Reinforcement Learning. The role involves developing unified modeling frameworks and exploring RL-based approaches for multimodal visual reasoning and instruction-conditioned generation, aiming for human-level understanding and interaction capabilities.

Research Scientist focused on developing computer vision, NLP, and LLM algorithms for next-generation VR intelligent interaction, including input methods, prediction, error correction, and multimodal fusion. The role involves delivering technical innovations, patents, and research translation, with a focus on lightweight models for VR/edge devices.

Seeking an experienced Research Scientist/Engineer to design and build next-generation AI infrastructure at ByteDance, focusing on large-scale systems, AI, and emerging hardware to enable efficient and scalable AI workloads. The role involves architecting the end-to-end AI factory, exploring emerging trends, optimizing ML stack performance, and aligning cross-functional teams.

Research Scientist role focused on developing multimodal large language models (MLLM) with tool-use capabilities for Mixed Reality (MR) environments. This involves optimizing model architectures, enabling tool utilization for complex tasks, and addressing challenges in long-horizon, multi-turn interactions. The role also includes applying and deploying innovative technologies in PICO's MR products and collaborating with cross-functional teams.

Research Engineer/Scientist focused on developing efficient algorithms and architectures for large-scale generative and multimodal models, with an emphasis on model distillation, compression, and hardware-efficient inference for applications like image generation, video generation, and VLMs.

Research Engineer/Scientist focused on applied research in Generative AI and CV/Multimodal Understanding, specifically on designing and implementing efficient models for large-scale generative AI through techniques like distillation and compression. The role involves developing methods and infrastructure for transferring capabilities from foundation models into smaller, more efficient models for scalable training, optimization, and deployment, with applications in image generation, video generation, and VLM.

Research Engineer/Scientist focused on applied research in Generative AI and CV/Multimodal Understanding, specifically on designing and implementing efficient models for large-scale generative AI through techniques like distillation and compression. The role involves developing methods and infrastructure for transferring capabilities from foundation models into smaller, more efficient models, enabling scalable training, optimization, and deployment, with applications in image generation, video generation, and VLMs.

Research Scientist/Engineer role focused on defining and building next-generation AI infrastructure for large-scale AI workloads, including training, RL, and inference, considering compute, storage, networking, chips, power, and data layers. The role involves tracking AI trends, optimizing system performance, and aligning cross-functional teams.

Research Scientist role focused on applied research in Generative AI and Computer Vision/Multimodal Understanding, with the goal of delivering intelligent solutions to ByteDance products. The role involves conducting cutting-edge research, transferring advanced technologies, and exploring new AI-centric products, with a focus on generative models for content creation, image/video synthesis, editing, and virtual humans.

Research Scientist focused on foundational models for visual generation and multimodal generative models. The role involves research and development to enhance strategic advantages for ByteDance products, with a focus on computer vision challenges. Experience with large-scale training and deep learning frameworks is preferred.

Research Scientist focused on foundation models for speech understanding, with a focus on pre-training and fine-tuning. The role involves research and development, collaboration with cross-functional teams, and integration of research findings into practical applications. The team works on multimodal speech technologies, including ASR, speech translation, self-supervised learning, and LLM pre-training/fine-tuning.

Research Scientist role at ByteDance focusing on multimodal AI for intelligent editing, involving large-scale training and RLHF, with a strong emphasis on computer vision and language understanding.

Research Scientist role focusing on multimodal understanding, vision and language, large-scale training, and RLHF for intelligent editing within ByteDance's Intelligent Creation Team. The role involves cutting-edge research and transferring technologies to products.

Research Scientist role focused on advancing next-generation LLMs, including pre-training, post-training, inference, and interpretability. The role involves exploring large-scale models, optimizing systems, data construction, instruction tuning, preference alignment, and improving model capabilities like reasoning and code generation.

Research Scientist role focused on building and scaling machine learning models for recommendation systems, including end-to-end generative systems and reinforcement learning for personalization. The role involves researching and applying multi-modal techniques, optimizing model architectures for large-scale training and inference, and collaborating with product and engineering teams for deployment. Requires expertise in deep learning, LLMs, multi-modal learning, and production ML pipelines, with a strong publication record.

Research and development role focusing on 3D Avatar generative models, involving 3D geometry, texturing, human reconstruction, and animation techniques. Requires expertise in generative modeling for 3D/4D reconstruction/generation, with a Master's degree or above and proficiency in deep learning frameworks.

Research Engineer/Scientist focused on designing and implementing a high-performance KV cache layer for LLM inference to improve latency, throughput, and cost-efficiency in transformer-based model serving.

Research Engineer/Scientist focused on applying AI/ML to database management systems, including query optimization, indexing, workload forecasting, and developing self-managing databases. The role involves integrating AI models into production systems and publishing research findings.

Research Engineer/Scientist role focusing on applying AI/ML to database management systems, including query optimization, indexing, workload forecasting, and developing self-managing databases. The role involves research and development, integrating AI models into production systems, analyzing large datasets, and publishing findings. Requires a PhD and strong publication record in AI/databases/systems, with experience in database internals and ML frameworks.

Research Engineer/Scientist focused on applying AI/ML to database management systems, including query optimization, indexing, and workload forecasting, with a goal of building AI-native data infrastructure and intelligent optimization. The role involves research and development, integrating models into production, and publishing findings.

Research Engineer focused on AI for 3D digital content creation, specifically human face and body, involving generative models and representations like NeRF. The role involves research, development, and transferring technology to products.

Research Scientist focused on AI security, investigating threats like adversarial attacks and model tampering, and developing mitigation strategies for NLP and computer vision models. Requires experience in AI/ML security research and programming skills.

Research Scientist role focusing on operations research for AI-native data infrastructure. The role involves designing and optimizing vector indexing algorithms for vector databases, and exploring the integration of LLM, RL, and Agent technologies into operations research optimization pipelines. This includes developing AI for infrastructure optimization and LLM-based tooling like NL2SQL.

Research Scientist role focused on designing and optimizing state-of-the-art vector indexing algorithms for next-generation vector database infrastructure, and exploring AI for Operations Research by integrating LLM, RL, and Agent technologies into optimization pipelines.

Research Scientist role focused on operations research for AI-native data infrastructure, including next-generation databases, AI for infra optimization, and LLM-based tooling. The role involves designing and optimizing vector indexing algorithms and exploring AI integration into operations research pipelines.

Research Scientist role focused on designing and optimizing state-of-the-art vector indexing algorithms and integrating AI (LLM, RL, Agent) into operations research optimization pipelines for AI data centers and cloud resource scheduling. The role involves building next-generation AI-native data infrastructure, including vector databases and intelligent algorithms for infrastructure optimization.

Research Scientist focused on DPU and AI infrastructure, aiming to accelerate distributed training and inference by co-designing software and hardware solutions. Explores AI/ML infrastructure acceleration leveraging DPUs, GPUs, and custom hardware.

Research Scientist role focused on designing and developing DPU network software for AI/ML workloads, optimizing distributed training and inference, and exploring software-hardware co-design for cloud and AI computing infrastructure.

Research Scientist role focused on designing and developing DPU network software for AI/ML workloads, including distributed training and inference acceleration, and software-hardware co-design.

This role focuses on designing and developing DPU network software and exploring AI/ML infrastructure acceleration using DPUs, GPUs, and custom hardware to optimize distributed training and inference. It involves software-hardware co-design and end-to-end performance optimization for cloud-scale computing.

Research role focused on designing and developing AI-powered video codec algorithms, optimizing performance, and pushing the boundaries of video coding technologies. The role involves foundational research into large models and next-generation standards for multimedia content.

Research and develop deep learning models for multimodal data fusion using sEMG, computer vision, and IMU technologies, focusing on signal acquisition, processing, and handling sensor noise for enhanced human-virtual world interaction.

Research Scientist role focused on designing and optimizing state-of-the-art vector indexing algorithms for large-scale similarity search and retrieval, powering next-generation vector databases. The work involves research into ANN search, optimization for performance, and collaboration with engineering for productionization, with a strong emphasis on academic publications and staying current with AI x systems research.

Research Scientist role focused on building AI-native data infrastructure, including VectorDBs, AI for infrastructure optimization, and LLM Copilot tooling. The role involves research, design, development, and publishing in top academic conferences.

Research Scientist focused on designing and optimizing state-of-the-art vector indexing algorithms for large-scale similarity search, filtered search, and hybrid retrieval use cases, contributing to next-generation vector database infrastructure. The role involves research and development of ANN algorithms, optimization for performance, and collaboration with engineering for productionization, with a strong emphasis on academic publications and staying current with AI x systems research.

Research Scientist focused on designing and optimizing state-of-the-art vector indexing algorithms for large-scale similarity search, filtered search, and hybrid retrieval use cases. The role involves developing new algorithms, optimizing for performance, and collaborating with engineering teams for productionization, with a strong emphasis on academic publications and staying current with AI x systems research.

Research role focused on developing AI imaging algorithms and perceptual metrics for AR/VR products, applying perception sciences, and designing eye-tracking features. Requires advanced degree, 5+ years experience, strong background in statistics, optimization, machine learning, and computational modeling, with experience in psychophysics and user studies.