Backend Engineer, AML Engine Orchestration

Backend Engineer, AML Engine Orchestration at TikTok in Singapore.

Responsibilities

Team Introduction

The mission of our AML team is to push next-generation machine learning algorithms and platforms for the recommendation system, ads ranking and search ranking in our company. We also drive substantial impact on core businesses of the company.

• Resource Efficiency Optimization in Distributed Orchestration and Scheduling:
• Develop and extend distributed orchestration frameworks within the Kubernetes/Godel ecosystem. Select appropriate frameworks based on different business scenarios, and optimize cluster utilization and load balancing strategies according to the specific characteristics of each scenario;
• Integrate and expand AutoScaling and automatic parallelization capabilities for various models and tasks. Employ load modeling and analytic methods for different models to automatically optimize resource requests, achieving large-scale improvements in resource usage efficiency and global optimality;
• Responsible for preemption and re-scheduling mechanisms for services with different prioritties, and manage automatic resource multiplexing across different clusters and resource types; handle scheduling and load adaptation across multi-datacenter, multi-region, and multi-cloud environments.
• Building Training System Architecture for Next-Generation Ultra-Large and Ultra-Deep Recommendation Models:
• Develop a flexible, elastic and robust distributed training runtime focused on hyper-scaled embeddings and large-scale GPU training;
• Design and optimize distributed computing APIs and runtimes geared towards future recommendation and ads model paradigms (e.g., reinforcement learning, fine-tuning and/or distillation);
• Collaborate with platform teams to enhance the diagnosability and usability of distributed training systems.
• Constructing Online Orchestration Architecture for Next-Generation Recommendation Systems:
• Build a robust distributed model inference architecture for online learning scenarios involving hyper-scaled embeddings;
• Optimize the usability of online recommendation and ads model architectures and MLops workflows.

Requirements

• Bachelor's degree or above, majoring in Computer Science, Engineering or related fields.
• Strong programming and coding experience with at least one modern language such as Golang, Python.
• Experience contributing to the large scale distributed systems, multi-tenant systems (architecture, reliability and scaling).
• Strong analytical abilities and problem solving.
• Good communication, self-motivation, engineering practice, documentation, etc.
• At least 3 years of relevant experience.

Preferred Qualifications

• Familiar with large-scale distributed scheduling systems like Kubernetes, Yarn, Flink and/or Spark
• Familiar with opensourced orchestration frameworks like VeRL, vLLM, Ray or TFX, etc.

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.