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Prepare coding and system design for backend services, ML pipeline trade-offs (latency vs cost), debugging under load, and how you would instrument an “efficiency tool” for real usage. Expect questions on collaboration in large product orgs and ownership on a graduate timeline toward 2027 start.
Strong fit if you like shipping backend for ML systems in Singapore at scale; weaker if you want pure research or remote-only work (listing is on-site Regular).
As a Backend Applied Machine Learning Engineer Graduate on an AML Efficiency Tool track at ByteDance Singapore (2027 start), expect backend services for model/tooling workflows: APIs and data paths that support training or inference efficiency, metrics for latency/cost/throughput, code reviews, and tight iteration with ML and product partners on production reliability rather than research papers alone.
Prioritize production backend (services, APIs, reliability), ML system efficiency (batching, caching, profiling), data pipelines, and clear experiment metrics. No certificate list or costs were provided for this family.
No—the listing is Singapore Regular with remote flagged off.
The title specifies a 2027 start for Bachelor/Master graduates.
Backend engineering that makes applied ML tooling more efficient and production-ready, not a salary or review guarantee.
Website: bytedance.com
ByteDance is a Chinese internet technology company headquartered in Haidian, Beijing. Its associated variable-interest entity, ByteDance Ltd, is incorporated in the Cayman Islands.
Public cache only — not an employee review.
Backend Applied Machine Learning Engineer Graduate (AML Efficiency Tool) - 2027 StartByteDance, Singapore What This Role Involves The Backend Applied Machine Learning team at ByteDance combines system engineering and machine learning to develop and run large-scale recommendation systems globally. As a graduate, you will have the opportunity to refine your coding skills, perform in-depth performance analysis, and collaborate with cross-functional teams to enhance our AML efficiency tools. Your Responsibilities Contribute to the development of efficient backend systems for machine learning models Analyze system performance and optimize code to improve speed and scalability Collaborate with data scientists, engineers, and product managers to deliver high-quality solutions Implement and maintain robust infrastructure supporting large-scale distributed systems Qualifications Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field (expected graduation 2027) Strong programming skills with experience in Python and/or other backend languages Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn is a plus Experience with distributed systems and cloud platforms like AWS, GCP, or Azure is beneficial Aptitude for problem-solving and ability to work in a fast-paced environment More About ByteDance ByteDance is a global technology company known for its innovative products and services. Our mission is to inspire creativity and bring joy to people around the world. With a focus on research, development, and engineering, we are committed to fostering an inclusive and collaborative work environment where talented individuals can thrive. Apply Today To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there. We look forward to hearing from you!
Generated for personal interview prep · 2026-08-14 UTC · getajob.ai