Backend Engineer Graduate (Recommendation Architecture) - 2026 Start (Phd)

About Us Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.​ Why Join ByteDance Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.​ As ByteDancers, 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. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.​ Diversity & Inclusion​ ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.​ Job highlights Yoga and fitness, Stock options, Positive team atmosphere, Career growth opportunity, Paid leave, Flat organization, 100+ mil users, Industry experts, Competitive compensation, Flexible hours Responsibilities Team Introduction Our Recommendation Architecture Team is responsible for building and optimizing the architecture of the recommendation system to provide the most stable and best experience for users. The team focuses on optimizing the recommendation system architecture, ensuring stability and high availability, and improving the performance of both online services and offline data flows. Collaborating with the algorithm team, we work to enhance recommendation effectiveness and user experience, boost system performance while reducing costs, build data and service mid-platforms, and realize flexible and scalable high-performance storage and computing systems. We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company. Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume. Responsibilities 1. 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. 2. 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. 3. 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. 4. 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. Meanwhile, ensure data privacy, security, and compliance. 5. 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. Deeply explore the quantitative relationship between data quality and model prediction performance, and build data-model correlation analysis tools and automa…