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Expect coding (Python/data structures), ML fundamentals, and recsys scenarios: cold start, bias/feedback loops, and metric choice. Prepare 1–2 projects where you defined a ranking or retrieval problem, measured lift, and explained failure modes. Be ready to discuss why a simple baseline might beat a complex model under latency constraints.
Best fit if you want hands-on recsys work at TikTok in Singapore, thrive on experimentation, and can grow from guided tasks to owning slices of the ranking stack. Less ideal if you need fully remote work or purely research-only scope without production constraints.
As a Graduate ML Engineer focused on recommendation systems at TikTok Pte. Ltd. in Singapore, a typical day centers on learning production recsys patterns: reading feature and ranking pipelines, running offline experiments, and shipping small model or data changes under senior review. You may analyze engagement signals, debug offline–online metric gaps, pair on code reviews, and document experiments so candidates and ranking quality stay measurable.
Prioritize supervised learning, embeddings, candidate generation and ranking, A/B testing, and Python plus common ML tooling. Practice offline metrics (e.g., AUC, NDCG) and simple online experiment design. No specific certification list or costs were provided for this listing.
The listing marks remote as no, with location Singapore—plan for on-site or hybrid expectations unless TikTok confirms otherwise in the offer process.
Coursework or projects in ML, recommendations or ranking, strong Python, and comfort reading experimental results matter more than a long cert list for a graduate seat.
Refresh ranking metrics, classic collaborative filtering vs. two-tower/embedding approaches, and be able to walk through an end-to-end experiment from data to offline eval to a cautious rollout plan.
TikTok Pte. Ltd. – Singapore About the Role We are seeking a Graduate Machine Learning Engineer to join our recommendations team at TikTok Pte. Ltd., based in Singapore. As part of this role, you will contribute to building and refining top-tier recommendation systems using machine learning techniques. You will work closely with the Recommendation Systems team to develop scalable classifiers and tools that support product goals. Day-to-Day Responsibilities Analyze user behavior to inform model development and refinement Develop, train, and deploy machine learning models for recommendation systems Create and maintain scalable ML pipelines and infrastructure Collaborate with cross-functional teams to ensure alignment with product goals Conduct experiments to optimize performance of recommendation algorithms Skills & Qualifications Relevant degree in Computer Science, Mathematics, Statistics, or a related field Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch) Experience with data preprocessing, feature engineering, and model evaluation techniques Strong programming skills in Python or similar languages Understanding of recommendation systems and their applications Excellent problem-solving and analytical skills Ability to work effectively in a fast-paced environment More About TikTok Pte. Ltd. TikTok Pte. Ltd., based in Singapore, is committed to fostering an innovative and inclusive workplace where creativity thrives. Our team of experts collaborates on cutting-edge projects that push the boundaries of technology and user experience. We value diversity and encourage individuals with a passion for innovation to join our ranks. Ready to Apply? To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there.
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