Site Reliability Engineer - Machine Learning Systems (Singapore)

BYTEDANCE PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

ByteDance is seeking a qualified engineer to join the Large Model Team in Singapore. You will help deploy and operate large-scale ML systems, focusing on training, evaluation and inference across multi-data center environments.

You will work with a global team to ensure system reliability, optimize resource usage and contribute to the ongoing development of distributed ML infrastructure. A strong background in Kubernetes, Linux and container technologies is essential.

Qualifications

• Bachelor's degree or higher in Computer Science, Computer Engineering or related field.
• Strong proficiency in at least one programming language (Go, Python or Shell) in a Linux environment.
• Hands-on experience with Kubernetes and containers; 1+ year of O&M experience.
• Experience in operation and maintenance of large-scale ML distributed systems is preferred.

Responsibilities

• Ensure ML systems operate efficiently for deployment, training, evaluation and inference.
• Maintain offline tasks/services across multiple data centers and regions.
• Manage resources, costs and budgets for computing and storage.
• Ensure global disaster recovery and stability of services across clusters.
• Build tools and systems to monitor and manage ML infrastructure and services.
• Be part of a global team providing on-call support.

Skills

Go

Python

Shell

Linux

Kubernetes

Containers

Education

Bachelor's degree in CS/CE or related

Tools

Kubernetes

Containers

Linux

Job description

Responsibilities

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.

Responsibilities

• Responsible for ensuring our ML systems are operating and running efficiently for large model deployment, training, evaluation, and inference
• Responsible for the stability of offline tasks/services in multi-data center, multi-region, and multi-cloud scenarios
• Responsible for resource management and planning, cost and budget, including computing and storage resources
• Responsible for global system disaster recovery, cluster machine governance, stability of business services, resource utilisation improvement and operation efficiency improvement
• Build software tools, products and systems to monitor and manage the ML infrastructure and services efficiently
• Be part of the global team roster that ensures system and business on-call support

Qualifications

Minimum Qualification(s)

• Bachelor's degree or above, majoring in Computer Science, computer engineering or related fields;
• Strong proficiency in at least one programming language such as

Go/Python/Shell in Linux environment;

• Strong hands-on experience with Kubernetes and containers skills, and have more than 1 year of relevant operation and maintenance experience; Preferred Qualification(s)
• Engage in the operation and maintenance of large-scale ML distributed systems;
• Experience in operation and maintenance of GPU servers
• Possess excellent logical analysis ability, able to reasonably abstract and split business logic, a strong sense of responsibility, good learning ability, communication ability, self-driven and good team spirit;
• Have good documentation principles and habits to be able to write and update workflow and technical documentation as required on time.

Job Information

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico 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 ByteDance

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.

As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

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.