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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Recommendation Architecture AI/ML Infrastructure Engineer Graduate (Data-Arch-TikTok Live) - 2027 Start - **Company:** Tiktok Inc. - **Location:** San Jose, CA, United States - **Experience:** Starter - **Salary:** $128,000.0 - $256,000.0 - **Contract:** Internship / Graduate position - **Skills:** Artificial Intelligence, C++ (Programming Language), Nvidia CUDA, Computer Programming, Computer Engineering, Data Structures, Distributed Systems, Python (Programming Language), Open Source Technology, Tensorflow, Software Engineering, Pytorch, Large Language Models, Gpu Programming, Information Technology, Machine Learning Operations - **Published:** August 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=72de31fdf0cb5f3b ## About the Role * Individuals who are completing or have recently completed a Bachelor's or Master's degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline. * Strong programming skills in C++ or Python. *Good understanding of data structures, algorithms, and computer systems. * Familiarity with PyTorch or TensorFlow. * Knowledge of Transformer architectures and Large Language Models (LLMs). * Strong problem-solving skills and a passion for building large-scale AI systems., * Hands-on experience with LLM training or inference through research, internships, or open-source projects. *Familiarity with distributed training concepts (e.g., DP, TP, PP, FSDP, ZeRO). * Experience with GPU programming using CUDA, Triton, or similar technologies. * Understanding of LLM serving techniques such as KV Cache, Continuous Batching, or FlashAttention. *Contributions to open-source projects or research in machine learning systems, distributed systems, or LLM infrastructure., Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment ## Description 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. Online Assessment Candidates who pass resume screening will be invited to participate in Our Company's technical online assessment. Responsibilities * Build and optimize infrastructure for large-scale model training and online inference. * Develop distributed systems supporting large recommendation models and LLMs. * Improve training and inference performance through GPU optimization and efficient communication. * Collaborate with researchers to develop and deploy LLM training and serving solutions. * Analyze system bottlenecks and implement performance optimizations. ## Related Videos - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)