Machine Learning Engineer - Singapore - TIKTOK PTE. LTD.

Description

Responsibilities

About TikTok

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul, and Tokyo.

Why Join Us

Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.

Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.

To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.

At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.

Join us.

Team Introduction

The Technical Infrastructure NoSQL team, situated in Singapore, serves TikTok and its associated mid-platforms and business divisions. This team operates on an immense scale, overseeing tens of thousands of servers and managing data volumes surpassing the petabyte mark. The team has engineered its own distributed key-value (KV) and caching systems, as well as globally distributed table storage solutions and large-scale graph databases. Employing state-of-the-art hardware and software stack technologies, they are committed to the ongoing development of the next generation of products.

What you will be doing:

1. Design and develop an in-house distributed training and inference system for Graph Neural Networks (GNNs) on extensive graph datasets;

2. Implement the use of Graph Embedding and GNNs in practical, real-world applications, which may include risk management, among others;

3. Integrate TikTok's diverse application contexts, such as recommendation, search, and risk control, to design, implement, and optimize neural network algorithm models. The objective is to leverage the GE/GNN approach for tangible business advantages in data-driven real-world scenarios;

4. Investigate potential advancements in graph neural network algorithms. Collaborate in the development of graph neural network frameworks;

5. Plan and lead the development of new and advanced data analytic techniques, methodologies, and analytical solutions from design, prototyping, and testing;

6. Extract and integrate data from various sources, and create advanced models and algorithms suitable for the business use case;

7. Work in a team setting and apply proficiency in statistics, scripting, and programming languages required by the team;

8. Work with relevant software platforms on which the solution is deployed.

Qualifications

What you should have:

At least a Bachelor's, Master's, or Ph.D. degree in Computer Science or a related field with 4 years of relevant experience;

Proficiency in Python development and a basic understanding of C++ programming;

Knowledgeable in TensorFlow and PyTorch, with hands-on experience in implementing popular Graph Embedding (GE) and Graph Neural Network (GNN) algorithms such as GCN, GraphSage, GAT, DeepWalk, LINE, etc. This experience should be based on existing GNN frameworks like DGL, PYG, or the native TensorFlow and PyTorch platforms.

Previous exposure to applying GNN models to address challenges in domains such as risk management, recommendation systems, e-commerce, finance, etc.

Effective communication skills and a collaborative team-oriented mindset.

Bonus: Preference is given to candidates who have authored academic papers related to GNN algorithms published in top AI conferences like ICML, ICLR, AAAI, NeurIPS, IJCAI, etc.

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.