Big Data Engineer Graduate (TikTok Recommendation Architecture) - 2027 Start

TIKTOK PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Yoga and fitness

Stock options

Positive team atmosphere

Career growth opportunity

Paid leave

Flat organization

100+ mil users

Industry experts

Competitive compensation

Flexible hours

Job summary

TikTok is seeking a talented engineer to join our Recommendation Architecture Team in Singapore. You will design and optimize the architecture of our recommendation system to ensure stability, high availability, and scalable performance across online services and offline data flows.

As a graduate or early-career professional, you will have opportunities to tackle bold ideas, grow rapidly, and contribute to a globally distributed team working on cutting-edge AI, big data, and ML technologies.

Qualifications

• Individuals who are completing or have recently completed a Bachelor's or Master's degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline.
• Familiar with many open source frameworks in the field of big data, e.g.Hadoop, Hive,Flink, FlinkSQL,Spark, Kafka, HBase, Redis, RocksDB, ElasticSearch etc.
• Familiar with Java, C ++ and other programming languages
• Strong coding and trouble shooting ability

Responsibilities

• Design and implement offline data architectures for large-scale recommendation systems.
• Build flexible, scalable, and high-performance storage and computing systems.
• Ensure production system stability through troubleshooting and tooling development.
• Develop data analytics and visualization capabilities to transform raw data into meaningful insights.
• Apply data mining, machine learning, and NLP to extract insights from large-scale datasets.

Skills

Java

C++

Education

Bachelor's or Master's in AI/Software Development/CS

Tools

Hadoop

Hive

Flink

Spark

Kafka

Job description

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

• 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. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

• Design and implement offline data architectures for large-scale recommendation systems.


• Build flexible, scalable, and high-performance storage and computing systems.


• Ensure production system stability through troubleshooting and tooling development.


• Develop data analytics and visualization capabilities to transform raw data into meaningful insights.


• Apply data mining, machine learning, and NLP to extract insights from large-scale datasets.

Qualifications

Minimum Qualifications

• Individuals who are completing or have recently completed a Bachelor's or Master's degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline.


• Familiar with many open source frameworks in the field of big data, e.g.Hadoop, Hive,Flink, FlinkSQL,Spark, Kafka, HBase, Redis, RocksDB, ElasticSearch etc.


• Familiar with Java, C ++ and other programming languages


• Strong coding and trouble shooting ability

Preferred Qualifications

• Agile, quick self learner, highly self-motivated with strong sense of product ownership and creative problem solver.


• Good collaborator and team player, comfortable working in a fast moving, culturally diverse and globally distributed team environment.