Software Engineer Graduate (AI Applications) - 2026 Start (BS/MS)
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About this role
About the team:
The Speech team's mission is to empower content interaction and creation using speech & audio related technologies. The team focuses on cutting-edge R&D in areas like speech & audio, music processing, natural language understanding and multimodal deep learning. We are looking for top talents to work on these exciting technologies, integrate them into various products and ultimately bring joy to our global user base!
We are seeking a passionate AI Model Optimization Engineer to join our team. In this role, you will design and implement cutting-edge techniques to make AI models faster, more efficient, and easier to deploy at scale. You will collaborate across research and engineering to push the limits of AI performance in production environments.
Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to ByteDance and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities:
- Responsible for the development of large-scale AI systems, solving technical difficulties such as high concurrency, high reliability, and high scalability of the system.
- Optimize deep learning models for lower latency, targeting backend server deployment.
- Work with researchers to land advanced technologies to ByteDance products.
- Build automation frameworks and tools to ensure high engineering quality and efficiency.
Minimum Qualifications:
- Currently pursuing a BS/MS in Software Development, Computer Science, Computer Engineering, or a related technical discipline
- Experience in python/C++ and solid software engineering background.
- Experience with deep learning frameworks (PyTorch, TensorFlow, JAX) and distributed training systems.
- Solid understanding of computer architecture, parallel computing, and GPU acceleration.
Preferred Qualifications:
- Familiarity with GPU programming (CUDA, Triton, or similar) is a plus.
- Familiarity with ML compilers (e.g., TVM, XLA, TensorRT) is a plus.
- Strong analytical skills and ability to work in a fast-paced team environment.