Research Scientist, AI Infrastructure & Distributed ML

Bytedance; San Jose, Northern (CA, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

ByteDance Doubao (Seed) seeks graduates to design scalable infrastructure for large-scale model training and inference. You will optimize distributed training across compute, memory, and communication, and improve reliability and observability for huge workloads. Collaboration across teams helps advance foundation models and ML systems.

You will contribute to evaluation, data processing, and lifecycle management, co-designing systems and algorithms to boost performance of foundation models.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline.
• Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc.
• Demonstrated interest or project experience in relevant areas.

Responsibilities

• Design and build scalable infrastructure for large-scale model training, evaluation, and inference.
• Optimize distributed training systems across compute, memory, and communication.
• Improve system reliability, efficiency, and observability for large-scale workloads.
• Develop frameworks for evaluation, data processing, and model lifecycle management.
• Co-design systems and algorithms to improve performance of foundation models.

Skills

C/C++

Python

Distributed systems

ML systems

Data structures

Algorithms

Collaboration

Education

Bachelor's degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or related discipline

Tools

C/C++

Python

Job description

ByteDance Doubao (Seed) seeks graduates to design scalable infrastructure for large-scale model training and inference. You will optimize distributed training across compute, memory, and communication, and improve reliability and observability for huge workloads. Collaboration across teams helps advance foundation models and ML systems.

You will contribute to evaluation, data processing, and lifecycle management, co-designing systems and algorithms to boost performance of foundation models.