Deskripsi Pekerjaan
Are you passionate about building scalable infrastructure that powers global AI innovations? ByteDance is looking for a highly skilled Backend Engineer to join our Applied Machine Learning (AML) Platform team in Singapore. In this role, you will be at the intersection of large-scale distributed systems and cutting-edge machine learning.
As a key member of the AML team, you will design, develop, and optimize robust platforms that support our machine learning lifecycles—from data processing and feature engineering to model training and inference. You will work alongside world-class engineers to solve complex engineering challenges, ensuring our platforms remain performant, reliable, and developer-friendly at a massive global scale.
If you thrive in a fast-paced environment and are eager to push the boundaries of what machine learning platforms can achieve, we invite you to apply and help shape the future of our intelligent systems.
Tanggung Jawab
- Design and implement scalable backend services and microservices to support machine learning workflows.
- Optimize the performance, availability, and reliability of the internal ML platform architecture.
- Collaborate with Data Scientists and Research Engineers to translate technical requirements into robust platform features.
- Develop and maintain APIs and SDKs to improve the developer experience for internal ML teams.
- Manage end-to-end deployment pipelines and infrastructure automation for model training and serving.
- Monitor platform metrics, troubleshoot production issues, and implement proactive system improvements.
- Contribute to the technical design and architectural planning of next-generation distributed ML systems.
Kualifikasi
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
- 3+ years of professional experience in backend development using languages such as Go, Java, C++, or Python.
- Deep understanding of distributed systems, concurrency, and high-performance computing.
- Solid experience with cloud-native technologies (e.g., Kubernetes, Docker) and container orchestration.
- Hands-on experience with databases (SQL/NoSQL) and message queues like Kafka or Pulsar.
- Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and MLOps principles is highly preferred.
- Strong problem-solving skills and the ability to work effectively in a global, collaborative team environment.