Machine Learning Engineer Graduate (Global E-Commerce, Recommendation) - 2027 Start (PhD)

TIKTOK PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

TikTok in Singapore is seeking a PhD-level software/ML researcher to join our E-commerce recommendation team. You will work on building billion-level recommendation algorithms, optimizing models, and deploying real-time ML pipelines.

Ideal candidates have strong programming skills and experience with TensorFlow or PyTorch, plus a track record in ML with large-scale data. This role offers an exciting chance to impact global e-commerce experiences.

Qualifications

• PhD or near completion in a technical discipline (CS/SE/CE).
• Strong programming and problem-solving ability.
• Experience in applied ML with common algorithms (CF, Matrix Factorization, LR, DNNs).
• Experience with DL tools such as TensorFlow or PyTorch.
• Proficiency in C++ or Python.

Responsibilities

• Build large-scale E-commerce recommendation algorithms and systems.
• Develop long/short-term user interest models from large data.
• Design and optimize predictive models for candidate generation and ranking.
• Create tools to support debugging and model deployment.
• Support production ML models and scalable data pipelines.
• Process real-time, unstructured data for AI/ML deployments.
• Run experiments to evaluate deployed models and fix issues.
• Collaborate in a team using statistics, scripting, and programming languages.
• Work with platforms where models are deployed.

Skills

Strong programming and problem solving

Applied machine learning

Deep learning (TensorFlow/PyTorch)

C++/Python proficiency

Education

PhD in Software Development, CS, or related field

Tools

TensorFlow

PyTorch

Job description

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.

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.About the Team

About the Team

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. We are a group of applied machine learning engineers and data scientists that focus on E-commerce recommendations. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested and excited in applying large scale machine learning to solve various real-world problems in E-commerce.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

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.

Responsibilities

• 1. Participate in building large-scale (billion level) E-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc.
• 2. Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
• 3. Design, develop, evaluate and iterate on predictive models for candidate generation and ranking(eg. Click Through Rate and Conversion Rate prediction) , including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation.
• 4. Design and build supporting/debugging tools as needed.
• 5. Support the production of scalable and optimised AI/machine learning (ML) models.
• 6. Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models.
• 7. Run experiments to test the performance of deployed models, and identify and resolve bugs that arise in the process.
• 8. Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm.
• 9. Work with the relevant software platforms in which the models are deployed.

Qualifications

Minimum Qualifications

• 1. Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• 2. Strong programming and problem-solving ability.
• 3. Experience in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc.
• 4. Experience in Deep Learning Tools such as tensorflow/pytorch.
• 5. Experience with at least one programming language like C++/Python or equivalent.

Preferred Qualifications

• 1. Experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.
• 2. Publications at KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RecSys and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc.