Platform R&D Engineer, Recommendation System

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is 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 bring joy - a mission we work towards every day.

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. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. 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

TikTok 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 TikTok, our mission is to inspire creativity and bring joy. 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

Responsibilities

About The Team

The Recommendation Architecture Team is responsible for designing and developing recommendation system architectures for various products under the company. We ensure system stability and high availability, optimize performance for online services and offline data pipelines, address system bottlenecks, and reduce operational costs. We also abstract reusable system components and services to build recommendation and data middleware platforms, supporting rapid incubation of new products and empowering enterprise clients (ToB).

Responsibilities

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

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

3. 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.

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

5. Overhaul platform ecosystem architectures and develop data intelligence assistants.

Qualifications

Minimum Qualifications

1. Bachelor's degree or above, majoring in Computer Science, or related fields, with 1 years of experience in designing and developing large-scale systems.

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

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

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

Preferred Qualifications

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

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

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