Responsibilities
1. Continue to promote the engineering optimization and application of the latest technology of Doubao Voice Big Model 2. Responsible for the design and implementation of a highly available, scalable, and distributed machine learning platform to support efficient iterative updates of multi-regional voice-related business model services 3. Work closely with algorithm, engine, and backend engineers to understand the capacity building and deployment and operation and maintenance processes of the voice big model MaaS, and be responsible for/participate in the design, development, and maintenance of the machine learning platform 4. Continuously improve the efficiency and usability of the platform, reduce the cost of use, explore the cutting-edge machine learning related technologies in the industry, design and implement them into the machine learning platform.
Qualifications
1. Bachelor degree or above in computer science and related majors, more than 3 years of Go and Python project development experience 2. Solid programming foundation, good programming style, familiar with multi-threaded programming, distributed computing, network communication, memory management, design patterns 3. Familiar with MLOps related work and understand common voice technology 4. Have a strong desire to learn, have enough enthusiasm and curiosity for new technologies, and love AI technology 5. Have a strong sense of work responsibility, goal-oriented, result-driven, strong business awareness, independent problem-solving ability, good collaborative communication skills and self-motivation 6. Those with the following experience are preferred: experience in AI model engineering and MaaS project implementation, experience in distributed architecture design and development, or rich experience in architecture design. Bonus points: 1) Experience in AI model engineering and MaaS project implementation, involving model management, service deployment, and platform automation 2) Experience in distributed architecture design and development, familiar with big data technology stacks such as Hadoop, HDFS, and ClickHouse 3) Rich experience in architecture design, able to accurately and comprehensively understand the business, and design reasonable architecture solutions based on business development.
