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TikTok

Short-form video platform with ads

AI Infrastructure Engineer - Recommendation & LLM

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USAIn-person

About the Job

Requirements

  • A Bachelor's, Master's, or Ph.D. degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
  • At least 3 years of software engineering, machine learning systems, distributed systems, or related industry experience.
  • Strong programming skills in C++ or Python and experience building production-quality software.
  • Strong understanding of data structures, algorithms, operating systems, distributed systems, or computer architecture.
  • Hands-on experience with PyTorch, TensorFlow, or other machine learning frameworks.
  • Experience designing, developing, or optimizing large-scale production systems.

Responsibilities

  • Design, develop, and optimize large-scale AI training and online inference infrastructure for recommendation models and large language models.
  • Drive the architecture and implementation of distributed training and serving systems with high scalability, reliability, and efficiency.
  • Optimize end-to-end model performance across GPU computation, communication, memory, networking, and runtime systems.
  • Develop and optimize large language model training and serving infrastructure, including model parallelism, key-value cache, continuous batching, and efficient inference.
  • Work closely with researchers and algorithm engineers to productionize new model architectures and algorithms.
  • Identify and resolve performance bottlenecks across the full AI stack, from models and frameworks to GPU kernels and distributed runtimes.
  • Improve system latency, throughput, GPU utilization, scalability, and infrastructure cost efficiency.
  • Drive technical design, implementation, performance benchmarking, and production rollout of critical infrastructure components.
  • Mentor junior engineers and contribute to the team's technical direction and engineering standards.

Desired Qualifications

  • Experience building infrastructure for large-scale recommendation systems, large language models, or foundation models.
  • Strong understanding of distributed training and model parallelism, including data parallelism, tensor parallelism, pipeline parallelism, Fully Sharded Data Parallel, Zero Redundancy Optimizer, or related technologies.
  • Hands-on experience with GPU programming and optimization, including CUDA, Triton, GPU kernels, or similar technologies.
  • Experience with large language model inference and serving, including key-value cache, continuous batching, FlashAttention, CUDA Graph, speculative decoding, or related techniques.
  • Experience optimizing GPU utilization, memory efficiency, communication performance, latency, and throughput at scale.
  • Experience with distributed systems, high-performance computing, networking, or machine learning infrastructure.
  • Experience designing and owning large-scale production systems from architecture through deployment and operation.
  • Contributions to open-source projects, research publications, or technical projects in machine learning systems, distributed systems, GPU computing, or large language model infrastructure.
  • Experience mentoring engineers or leading technical projects.

About the Company

TikTok

Short-form video platform with ads

TikTok is a short-form mobile video platform that lets people create, discover, and share quick videos. Users upload vertical clips, edit them with built-in tools, and browse a personalized feed powered by an algorithm that highlights relevant content. Advertisers can use in-feed ads, branded hashtags, and the Business Center to plan and measure campaigns, making it easy for brands to reach a global audience. Its goal is to inspire creativity and bring joy by helping people express themselves and by connecting brands with a wide audience.

Company size
10,001+
Company stage
Grant
Total funding
$740K
Headquarters
Santa Monica, CA
Founded
2016

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