Senior Platform R&D Engineer - Recommendation System; ByteDance Job Singapore area,Singapore,Software Development

Position: Senior Platform R&D Engineer - Recommendation System (ByteDance )

About Us

Founded in 2012, Byte Dance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including Tik Tok, Lemon8, Cap Cut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, Byte Dance has made it easier and more fun for people to connect with, consume, and create content.

Why

Join Byte Dance

Inspiring creativity is at the core of Byte Dance'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.

Diversity & Inclusion

Byte Dance 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 Byte Dance, 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

Career growth opportunity
Paid leave
Flat organization

About the team

Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation system to provide the most stable and best experience for our users. Due to the big system scale and large engineering community that covers multiple Recommendation products, we invest heavily in the developer infra area, from developer environments and continuous integration/continuous deployment (CI/CD) to frameworks, libraries, and various productivity tools.

Responsibilities

Design intelligent development toolkits for large-scale recommendation systems, providing tooling and productized solutions to enhance R&D efficiency.

Develop business metrics-driven gray release systems to ensure safe, stable, and efficient release strategies and workflows.

Enhance observability of recommendation systems in complex global environments (multi-region, multi-data center, multi-language), establish end-to-end tracing systems, and optimize issue attribution mechanisms.

Build algorithm engineering tool chains to accelerate the end-to-end process from experimental algorithm/model development to deployment, improving iteration efficiency.

Overhaul platform ecosystem architectures and develop data intelligence assistants.

Qualifications

Minimum Qualifications

Bachelor's degree or above, majoring in Computer Science, or related fields, with 3+ years of experience in designing and developing large-scale systems.

Proficiency in at least one programming language (Go/Python/C++) and solid understanding of data structures and algorithms.

Ability to independently lead the technical design and implementation of complex systems and components.

Strong product sense, with the ability to balance priorities across requirements, technical solutions, timelines, and delivery quality.

Preferred Qualifications

Deep understanding of large language models (LLMs), familiarity with LLM principles and applications, and hands-on experience in Agent system design.

Experience in recommendation/advertising/search systems, or privacy compliance frameworks (GDPR, CCPA).

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