Software Engineer, ML System Scheduling

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok and Helo as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. ByteDance is a global incubator of platforms at the cutting edge of commerce, content, entertainment, and enterprise services - over 2.5 billion people interact with ByteDance products, including TikTok Why Join Us Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. Join us. Team Intro Founded in 2023, the ByteDance Doubao (Seed) Team, is dedicated to pioneering advanced AI foundation models. Our goal is to lead in cutting-edge research and drive technological and societal advancements. With a strong commitment to AI, our research areas span deep learning, reinforcement learning, Language, Vision, Audio, AI Infra and AI Safety. Our team has labs and research positions across China, Singapore, and the US. Leveraging substantial data and computing resources and through continued investment in these domains, we have developed a proprietary general-purpose model with multimodal capabilities. In the Chinese market, Doubao models power over 50 ByteDance apps and business lines, including Doubao, Coze, and Dreamina, and is available to external enterprise clients via Volcano Engine. Today, the Doubao app stands as the most widely used AIGC application in China. The Machine Learning (ML) System sub-team combines system engineering and the art of machine learning to develop and maintain massively distributed ML training and Inference system/services around the world, providing high-performance, highly reliable, scalable systems for LLM/AIGC/AGI. In our team, you'll have the opportunity to build the large-scale heterogeneous system integrating with GPU/NPU/RDMA/Storage and keep it running stable and reliable, enrich your expertise in coding, performance analysis and distributed system, and be involved in the decision-making process. You'll also be part of a global team with members from the United States, China and Singapore working collaboratively towards unified project direction. Responsibilities: 1. Responsible for the design and development of resource scheduling, including model training, model evaluation and model inference in various scenarios (LLM/AIGC/NLP/CV/Speech, etc.) 2. Responsible for the optimal orchestration of various computing resources (GPU, CPU, other heterogeneous hardware), realizing the rational use of stable resources, tidal resources, mixed resources, and multi-cloud resources 3. Responsible for the optimal combination of computing resources, RDMA high-speed network resources, and storage resources, and giving full play to the power of large-scale distributed clusters 4. Responsible for offline and online workload scheduling in global data centers integrating multi-cloud scenarios to achieve rational distributions

Minimum Qualifications: 1. Be proficient in 1 to 2 programming languages such as Go/Python/Shell in Linux environment 2. Be familiar with Kubernetes architecture and container technology such as Docker/Containerd/Kata/Podman, and have rich experience in Machine Learning system practice and development 3. Understand the principles of distributed systems and have experience in the design, development and maintenance of large-scale distributed systems 4. Have an excellent logical analysis ability, able to reasonably abstract and split business logic 5. Have a strong sense of responsibility, good learning ability, communication skills and self-drive, able to respond and act quickly Preferred Qualifications 1. Familiar with at least one major Machine Learning framework (TensorFlow/PyTorch) 2. Experience in one of the following fields: AI Infrastructure, HW/SW Co-Design, High Performance Computing, ML Hardware Architecture (GPU, Accelerators, Networking) TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at rd.accommodations@tiktok.com