Job description

The ads system at TikTok operates on a massive scale and serves millions of advertisers, clients and influencers across the world. The quality of the ads system highly depends on the ability to handle massive data, and machine learning is widely used to improve the quality of our ads. The Ads Infra team is responsible for building highly efficient and stable infrastructure to collect and process data for the usage of machine learning training, serving, and privacy enforcement, including feature engineering, feature store, training data generation, etc. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities: - Develop and optimize advertising recommendation models, covering training, evaluation, inference and user behavior sequence modeling. - Build large-scale data pipelines for sample generation and joining, feature processing, storage and data quality assurance. - Develop ML platforms for distributed training, model distribution, online serving and lifecycle management. - Explore MLLM applications in advertising, including data production, model training, fine-tuning and inference optimization. - Apply AI agents to workflow orchestration, resource scheduling, failure diagnosis and automated operations. - Build machine learning platforms for GPU allocation, scheduling, usage metering, cost accounting and utilization optimization. Minimum Qualifications - Individuals who are completing or have recently completed a Bachelor's/ Master's degree in Computer Science or a related discipline. - Proficiency in at least one programming language, such as C++, Python, Go or Java. - Solid knowledge of data structures, algorithms, machine learning and computer systems. - Familiarity with recommendation systems, MLLMs, distributed systems, ML platforms or large-scale data processing. - Experience with deep learning frameworks, distributed training, GPU scheduling, AI agents or cloud-native technologies is a plus. By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: careers.tiktok.com

Requirements

Must-haves

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Develop and optimize advertising recommendation models, covering training, evaluation, inference and user behavior sequence modeling.
Build large-scale data pipelines for sample generation and joining, feature processing, storage and data quality assurance.
Develop ML platforms for distributed training, model distribution, online serving and lifecycle management.
Explore MLLM applications in advertising, including data production, model training, fine-tuning and inference optimization.
Apply AI agents to workflow orchestration, resource scheduling, failure diagnosis and automated operations.
Build machine learning platforms for GPU allocation, scheduling, usage metering, cost accounting and utilization optimization.
Individuals who are completing or have recently completed a Bachelor's/ Master's degree in Computer Science or a related discipline.
Proficiency in at least one programming language, such as C++, Python, Go or Java.
Solid knowledge of data structures, algorithms, machine learning and computer systems.
Familiarity with recommendation systems, MLLMs, distributed systems, ML platforms or large-scale data processing.
By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

Nice-to-haves

Experience with deep learning frameworks, distributed training, GPU scheduling, AI agents or cloud-native technologies is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlaipythongojava

Platform: tiktok
Effort: medium