AI Infrastructure Optimization Engineer Intern (TikTok Global E-Commerce Recommendation & Searc[...]

TikTok; Singapore; On-site; SGD 20,000 - 27,000; Full time

Job summary

TikTok is seeking interns to join the E-commerce Recommendation Infra team in Singapore. You will research and implement LLM-based recommendation foundations, and build optimization toolchains for large-scale deployment in a fast-growing e-commerce context.

Candidates should be pursuing a CS/CE/IS degree and have hands-on experience with C++/CUDA/Python and DL frameworks like PyTorch or TensorFlow. Prior exposure to Megatron-LM or DeepSpeed is a plus.

Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline
• Solid programming skills in C++/CUDA/Python, with basic understanding of GPU architecture and distributed training
• Familiarity with deep learning frameworks (PyTorch, TensorFlow) and basic knowledge of LLMs

Responsibilities

• Research and implement LLM-based recommendation foundation model training and inference optimization technologies for e-commerce scenarios
• Build model optimization toolchains including quantization, pruning, and distillation for deep learning frameworks
• Design and implement distributed inference serving architectures supporting large-scale LLM deployment for recommendation use cases

Skills

C++/CUDA/Python

GPU architecture

Distributed training

Deep learning frameworks

LLM inference acceleration

Education

Bachelor’s or Master’s in CS/CE/IS

Tools

PyTorch

TensorFlow

Megatron-LM

DeepSpeed

TensorRT-LLM

Job description

Responsibilities

E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-commerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques. With the rapid development of LLM technologies, traditional deep learning algorithms and system architectures for recommendation are facing both transformational challenges and opportunities, including lifelong behavior modeling, model scale-up, and end-to-end generative recommendation.

Responsibilities

E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-commerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques. With the rapid development of LLM technologies, traditional deep learning algorithms and system architectures for recommendation are facing both transformational challenges and opportunities, including lifelong behavior modeling, model scale-up, and end-to-end generative recommendation.

Applications will be considered in the order they are submitted.

Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

Successful candidates must be able to commit to at least 3 months long internship period.

Responsibilities

• Research and implement LLM-based recommendation foundation model training and inference optimization technologies for e-commerce scenarios
• Build model optimization toolchains including quantization, pruning, and distillation for deep learning frameworks
• Design and implement distributed inference serving architectures supporting large-scale LLM deployment for recommendation use cases

Qualifications

Minimum Qualifications：

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline
• Solid programming skills in C++/CUDA/Python, with basic understanding of GPU architecture and distributed training
• Familiarity with deep learning frameworks (PyTorch, TensorFlow) and basic knowledge of LLMs

Preferred Qualifications

• Hands-on experience with LLM inference acceleration technologies (model quantization, KV cache optimization, FlashAttention)
• Practical experience using LLM systems such as Megatron-LM, DeepSpeed, vLLM, or TensorRT-LLM
• Interest in recommendation systems and generative AI technologies

Job Information

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.