Responsibilities
- Design, train, and fine-tune large language models supporting TRAE’s reasoning and code-generation capabilities.
- Build efficient, stable, and scalable model training and evaluation pipelines.
- Collaborate with infrastructure and product teams to deploy and monitor models on GPU clusters.
- Optimize models for latency, throughput, accuracy, quantization, pruning, and inference acceleration.
- Apply current techniques in large-model optimization and inference acceleration.
Requirements
- Bachelor’s degree or above in Computer Science, Electrical Engineering, Mathematics, or a related field.
- Strong foundation in machine learning, deep learning, and optimization algorithms.
- Proficiency with PyTorch or TensorFlow and programming skills in Python and C++/CUDA.
- Experience with large-scale distributed training, mixed-precision training, or model parallelism.
- Hands-on experience with model quantization, pruning, or CUDA-based deployment optimization.
- Passion for building efficient, production-ready AI systems.
- Preferred: PhD in an AI-related research field.
- Preferred: hands-on experience developing and deploying AI systems in real-world settings.
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About ByteDance
ByteDance is a global incubator of platforms at the cutting edge of commerce, content, entertainment and enterprise services - over 2.5bn people interact with ByteDance products including TikTok. Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. We are committed to building a safe, healthy and positive online environment for all our users. We have over 110,000 employees based in more than 30 countries globally. Join us.