Responsibilities
- Convert and compile machine learning models for execution on edge NPUs and apply quantization mechanisms.
- Profile and analyze model performance and power consumption on simulators, emulators, and silicon platforms.
- Identify compute, memory-bandwidth, data-movement, and scheduling bottlenecks.
- Apply hardware-aware optimization strategies including quantization, compression, and operator fusion to meet latency, memory, and power targets.
- Collaborate with algorithm, compiler, firmware, and hardware teams to debug functional and performance issues.
Requirements
- Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent practical experience.
- At least 3 years of industry experience in machine learning software engineering, model deployment, or production ML systems.
- Strong understanding of deep learning architectures, including CNNs and Transformers.
- Knowledge of ML accelerator architectures, operator fusion, memory hierarchies, and data movement.
- Practical experience with ML frameworks such as PyTorch or TensorFlow.
- Proficiency in Python and C/C++.
- Preferred: 5+ years of industry experience in machine learning software engineering, model deployment, or production ML systems.
- Preferred: understanding of edge-device inference constraints, including latency, power, and accuracy trade-offs.
- Preferred: understanding of quantization techniques such as PTQ and QAT.
Categories
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.