Recommendation System Architecture Engineer- Soaring Star Talent Program

Overview
Recommendation System Architecture Engineer- Soaring Star Talent Program at ByteDance
Join to apply for the
Recommendation System Architecture Engineer- Soaring Star Talent Program
role at
ByteDance .
Responsibilities
The ByteDance Recommendation Architecture Team is responsible for the design and development of the recommendation system architecture for ByteDance's related products. It ensures the stability and high availability of the system, optimizes the performance of online services and offline data streams, resolves system bottlenecks, and reduces cost overheads. The team also abstracts the common components and services of the system, builds the recommendation middle-office and data middle-office to support the rapid incubation of new products and enable ToB services.
Strategy Management and Optimization: Build an intelligent system to achieve standardized definition of recommendation strategies, long-term and offline evaluation, automatic identification and retirement of ineffective strategies, and removal of related code configurations.
Adaptive Tuning and Fault Diagnosis: Leverage large model capabilities to optimize parameters and configurations of systems and underlying components for diverse business loads in recommendation systems. Explore adaptive fault diagnosis solutions to provide global perspective for fault tracking, localization, and analysis.
Cost-Efficiency Balance: Address the high costs of model training and operation when applying generative technologies to recommendation systems, balancing costs and efficiency to achieve effective recommendation within limited resources.
Cross-Domain Data Processing: Handle massive heterogeneous data in horizontal cross-domain scenarios (e.g., e-commerce), improve and ensure data quality and accuracy, standardize data supply for cross-domain recommendation models, and enable low-cost cross-terminal services. Ensure data privacy, security, and compliance.
Data Storage and Quality Enhancement: Develop low-cost, high-performance storage engines, design flexible Schema Evolution mechanisms, achieve high-concurrency real-time data writing and training-inference consistency. Explore data quality and model prediction performance, and build data-model correlation analysis tools and automated training data processing pipelines based on Data-Centric AI (DCAI).
Multimodal Data and Heterogeneous Computing: Construct a multimodal data heterogeneous computing framework to solve challenges in data reading, framework integration, and high-performance operator orchestration, improving data processing and model training efficiency. Establish a developer ecosystem centered on Python.
Large-scale Computing Model Efficiency Optimization for Recommendation: With breakthroughs in large models across CV/NLP/multimodal fields, balance computing overhead and effectiveness through Co-Design by architecture and algorithm engineers.
Qualifications
Doctorate degree (PhD).
Preferred fields: Artificial Intelligence, Computer Science, Mathematics, and related interdisciplinary majors.
Academic achievements: Priority given to candidates with in-depth research results and extensive practical experience in relevant fields, such as outstanding performance in natural language processing, computer vision, data modeling, or algorithm optimization.
Coding skills: Excellent programming abilities with strong knowledge of data structures and fundamental algorithms. For traditional coding roles, proficiency in C/C++; for intelligent coding roles, proficiency in Python. Ability to implement complex algorithms and build iterative models; strong engineering mindset to balance performance and cost.
Machine learning skills: Strong foundation in machine learning, familiarity with commonly used models, and the ability to build, train, and optimize models. Familiar with latest AGI technologies and able to validate and explore their applications in e-commerce generative recommendation.
Communication and collaboration: Ability to effectively communicate and collaborate with algorithm engineers, data analysts, and product managers to explore new technologies and drive innovation in e-commerce generative recommendation systems.
Job Information
About TikTok
TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, with offices around the world.
Why Join Us
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Join us to create value for our communities and achieve meaningful breakthroughs together.
Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills and perspectives. We celebrate diverse voices and aim to reflect the communities we reach.
Seniority level
Internship
Employment type
Full-time
Job function
Information Technology
Industries
Software Development
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