Backend Engineer, Machine Learning Systems - Singapore

at  ByteDance

ByteDance will be prioritizing applicants who have a current right to work in Singapore, and do not require ByteDance sponsorship of a visa.
About ByteDance
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.
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.
About the team
The ByteDance Large Model Team is committed to developing the most advanced AI large model technology in the industry, becoming a world-class research team, and contributing to technological and social development. The Large Model Team has a long-term vision and determination in the field of AI, with research directions covering NLP, CV, speech, and other areas. Relying on the abundant data and computing resources of the platform, the team has continued to invest in relevant fields and has launched its own general large model, providing multi-modal capabilities.
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 steadily and reliably, 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.

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or above, major in Computer Science, computer engineering or related;
• Strong proficiency in at least one programming languages such as C++/Go/Python/Shell in Linux environment;
• Proven experience in contributing to large scale systems, multi-tenant systems including architecture, reliability and scaling;
• Strong hands-on experience with Kubernetes architecture, and possess rich experience in system-level development and tuning;
• Possesses Have an excellent logical analysis ability, able to reasonably abstract and split business logic;
• Have a strong sense of responsibility, good learning ability, communication ability and self-drive, good team spirit

PREFERRED QUALIFICATIONS:

• Familiar with the ML Infrastructure of Large Model training and inference
• Familiar with front-end and back-end technologies, such as Django / Flask / NodeJS / React, etc.;
• Experience in one of the following fields: AI Infrastructure, HW/SW Co-Design, High Performance Computing, ML Hardware Architecture (GPU, Accelerators, Networking)
  ByteDance 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 ByteDance, our mission is to inspire creativity and enrich life. 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

1. Responsible for the design and development of Machine Learning infrastructure and platform services for model development, training and deployment;
2. Build and deploy large scale systems for machine learning integrating with GPUs, RDMA networking, and high-performance storage;
3. Design and develop resource orchestration and workload scheduling in global data centers for online and offline scenarios;
4. Manage a large number of GPU resources to ensure computing powers are efficiently allocated to the different business lines;
5. Be the expert in providing technical solutions and consultations to business users for problems such as high stability and availability of the system;
6. Be the go-to expert to drive project deliverables for system and services construction with cross-functional teams such as business team, data center team, network team, computing team, storage team;
7. Research, design, and develop computer and network software or specialised utility programs;
8. Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis;
9. Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures;
10. Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements;