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Model Training Acceleration Engineer

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: TikTok
Apprenticeship/Internship position
Listed on 2026-06-19
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: Large Model Training Acceleration Engineer

Team Introduction

The Intelligent Creation - AI Platform team focuses on building advanced end-to-end AI production pipelines, including deep learning model training, optimization, deployment, and applications. We provide AI capabilities to empower content creation and consumption on Tik Tok and serve billions of users.

Role

We are seeking an experienced AI model optimization engineer with expertise in optimizing AI model training and inference, including distributed training/inference and acceleration. The ideal candidate will work at the cutting edge of AI efficiency, enhancing the performance, scalability, and deployment of large‑scale generative AI models.

Responsibilities
  • Optimize large model training pipelines to improve efficiency, speed, and scalability.
  • Develop and improve distributed training strategies such as data parallelism, model parallelism, pipeline parallelism, and communication to accelerate model training.
  • Benchmark and profile deep learning models to identify performance bottlenecks and optimize computational resources.
Minimum Qualifications
  • Master’s or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or a related field.
  • 5+ years of experience in AI model training optimization.
  • Strong software engineering skills, including proficiency in Python, C++, and CUDA.
  • Strong proficiency in deep learning frameworks such as PyTorch, Megatron, and Deepspeed.
  • Experience with distributed training techniques such as data parallelism, model parallelism, and pipeline parallelism.
  • Knowledge of transformers and diffusion models.
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