Machine Learning Engineer for an AI coding tool (TRAE) that acts as an intelligent engineer for software development. The role focuses on model training, optimization, quantization, and deployment of LLMs for code generation and reasoning capabilities, working on both training and deployment pipelines.

This role focuses on building and scaling the core memory infrastructure for AI agents. It involves designing, developing, and optimizing large-scale, low-latency systems for storing, retrieving, and updating memory, with a focus on multimodal data and integration with LLMs. The goal is to enable more personalized and context-aware AI experiences by creating a unified platform for various memory types.

This role focuses on building and scaling the core memory infrastructure for AI agents, enabling personalized and context-aware AI experiences. It involves designing and operating large-scale, low-latency systems for memory storage, retrieval, and optimization, working at the intersection of LLMs, data systems, and context engineering, with a focus on multimodal data fusion.

Senior Software Engineer to build and evolve next-generation memory infrastructure for AI agents, focusing on a unified platform for long-term, conversational, and task-oriented memory. This role involves architecting and optimizing large-scale, low-latency pipelines for data ingestion, storage, indexing, retrieval, and updating, working at the intersection of LLMs, context engineering, and data management. Responsibilities include designing unified memory models for multimodal data and collaborating with teams to productionize these capabilities.

Develops end-to-end visual intelligence algorithms for VR/MR/AR products, spanning on-device and cloud-based solutions, including computational imaging, computer vision, and large-model driven visual understanding. Owns algorithm design from research to deployment and system integration.

Senior Software Engineer to build AI-powered developer tools, focusing on retrieval infrastructure (RAG), a coding agent with multi-step capabilities and tool use, and evaluation frameworks for quality measurement. Requires strong Python/TypeScript, systems programming, and practical LLM integration experience.

The role focuses on building and architecting AI-native database systems that integrate various data types, optimize for embedding ingestion and multimodal retrieval, and serve as reasoning engines and memory backends for AI agents. It involves developing scalable vector search systems, AI-augmented query processors, and RAG infrastructure, with a strong emphasis on systems design and implementation in C++/Rust/Go.

The role focuses on building AI-native database systems that act as reasoning engines, retrieval platforms, and memory for AI agents. Responsibilities include architecting and implementing databases for structured, unstructured, and vectorized data, optimizing storage for embeddings and multimodal retrieval, building scalable vector search systems, developing AI-augmented query processors using LLMs, and collaborating on RAG infrastructure and agent memory backends. The role also involves driving innovation in learned index structures and self-optimizing databases, with an emphasis on systems for AI workloads.

This role focuses on building next-generation AI-native database systems that act as reasoning engines, retrieval platforms, and memory for AI agents. The engineer/researcher will architect and implement systems integrating various data types, optimize storage for embeddings, build vector search, develop AI-augmented query processors, and contribute to RAG infrastructure and LLM agent memory backends. The role also involves driving innovation in learned index structures and AI-integrated transaction systems, with opportunities for publication.

Software Engineer/Researcher to build and own AI-native database systems, acting as reasoning engines, retrieval platforms, and real-time memory for AI agents. The role involves architecting systems that integrate structured, unstructured, and vectorized data, optimizing storage for embeddings, building scalable vector search, developing AI-augmented query processors using LLMs, and collaborating on RAG infrastructure and LLM agent memory backends. Innovations in learned index structures and self-optimizing databases are also key.

Algorithm Tech Lead Manager for ByteDance's enterprise solutions, focusing on implementing LLMs, VLLMs, and AI Agents in business scenarios like intelligent recommendations and AI Copilots. The role involves designing and implementing data pipelines and algorithm applications, leading a team of algorithm engineers, and collaborating with product managers and business developers to enhance enterprise service construction.

Machine Learning Engineer focused on e-commerce governance, using GNNs, LLMs, and time series for fraud detection, quality control, and logistics optimization. The role involves building and deploying AI solutions to improve platform health, seller compliance, and user trust.

Tech Lead Manager for Large Language Models & Generative AI focusing on developing long-term memory capabilities and delivering personalized chat, search, and recommendation experiences. Responsibilities include developing advanced AI algorithms, improving natural language understanding, full-stack development of large-scale ML and recommendation systems, and applying LLM techniques for information finding. Requires strong coding, analytical skills, and experience with NLU, Recall, Sort, large-scale search, recommendation, and LLM systems.

Develops an AIOps platform for data center networking, focusing on building an intelligent diagnostics system, exploring LLM/Agent applications for operations, and establishing capacity prediction. Integrates streaming telemetry and applies ML/DL for anomaly detection and root cause analysis.

Develops and implements an AIOps platform for data center networking, leveraging LLMs and agents for intelligent diagnostics, automated remediation, and predictive capabilities. Focuses on building a panoramic network observability platform and applying ML/DL for anomaly detection and root cause analysis.

Software Development Engineer role focused on prototyping AI and XR product concepts, specifically agentic AI on mobile and smart devices. The role involves rapid software development and iteration across various platforms to validate product features and user experiences.

Senior Software Engineer to build AI-powered developer tools, focusing on retrieval infrastructure (RAG), a coding agent with multi-step generation and tool use, and evaluation frameworks for measuring effectiveness. Requires strong Python/TypeScript, systems-level language experience, and practical LLM integration.

Senior Software Engineer to build AI-powered developer tools that integrate AI/ML into the toolchain to accelerate software development, improve code quality, and simplify engineering workflows. Focus on intelligent assistants, static/dynamic analyzers, and smart automation features.

Security Software Engineer focused on threat detection and response (TDR) for large-scale platforms, with a specific emphasis on securing AI and LLM systems, including agent architectures. The role involves designing and building defensive frameworks, identifying attack surfaces, and ensuring the safe deployment of AI-powered products.

Senior Industrial Designer/Computational Designer with AI Design Engineering focus, responsible for incubating new product concepts by rapidly prototyping end-to-end user experiences that leverage emerging technologies. The role involves designing physical products as contextual nodes in a distributed AI system, prototyping both hardware and software to validate sensing, inference, feedback, and user behavior change loops. Key responsibilities include architecting AI contextual ecosystems, iterative design prototyping from 'works-like' to high-fidelity, defining sensor architecture for AI context perception, and developing a physical language for AI semantics. The role requires strong scripting/programming skills in Python and familiarity with AI-assisted workflows.