Algorithm Engineer Graduate (Global Live - Strategy) - 2027 Start (PhD)

TIKTOK PTE. LTD.; Singapore; On-site; SGD 66,960 - 122,760; Full time

Job summary

TikTok is seeking talented engineers and researchers in Singapore to work on real-time, high-performance distributed infrastructure for live streaming. You will collaborate with product managers to deliver the best LIVE experience and explore model-driven strategies for revenue and engagement.

Ideal candidates are pursuing a PhD in Computer Science or related fields, with strong C/C++/Python skills, ML knowledge, and experience with big data frameworks.

Qualifications

• PhD candidate in Computer Science or related engineering field.
• Proficient in C/C++ and Python; experience with Linux multi-threaded / multi-process.
• Knowledge of ML/DL algorithms including reinforcement learning.
• Strong statistical and data analysis skills.
• Experience with big data frameworks like Flink, Spark or Hive.

Responsibilities

• Contribute to optimization of ByteDance LIVE monetization and live experience for billions of users.
• Apply state-of-the-art ML models to model user behavior and build scalable services.
• Analyze user and system data to guide product and optimization decisions.

Skills

C/C++/Python development

Linux multi-threaded / multi-process

Machine learning algorithms

Big data frameworks

Education

PhD in Computer Science or related engineering

Tools

Flink

Spark

Hive

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, Six insurances and one fund, Five insurances and one fund, Stock options, Positive team atmosphere, Career growth opportunity, Paid leave, Flat organization, 100+ mil users, Industry experts, Meal allowance, Meals provided, Competitive compensation, Flexible hours, Housing subsidy

Responsibilities

With the enormous growth of live streaming in recent years, our mission is to inspire real-time interactions and help live streamers connect to people from all corners of the globe.

We are looking for passionate and talented engineers to join us to build and optimize a real-time, high-performance, large-scale distributed infrastructure for live streaming in TikTok. You will be deeply involved in the developmental lifecycle of critical product features and collaborate closely with product managers to deliver the best live streaming experience for all live streamers and audience alike.

The strategy team's mission is to use model-driven and data-driven ways to promote core indicators on LIVE revenue and user engagement, which includes:

• Build prediction/uplift NN model to improve LIVE feature intelligence;
• Mine and interfere potential crowds to gain a higher ROI operation for both LIVE streamer and watcher;
• Make detailed analysis on user data and system data to find out user experience optimization zoom;
• Other work like user growth strategy, cold-start strategy, etc.

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.

Job Description

• Participate in the optimization of ByteDance LIVE monetization business and serve the LIVE experience of billions of global users;
• Adopt cutting‑edge machine learning model to scientifically model massive user behaviour and consumption data, build high‑performance/high‑reliability architecture services, and bring users the ultimate experience in LIVE consumption;
• Deeply participate in product/business discussions, fully analyze and understand user behaviour patterns, and provide optimization directions for the overall business.
  

Qualifications

Minimum Qualifications:

• Currently pursuing a PhD in Computer Science or a related engineer discipline.
• Familiar with C/C++/ Python development, familiar with Linux multi‑threaded /multi‑process;
• Familiar with commonly used machine learning and deep learning algorithms, including but not limited to boost machine, dnn, reinforcement learning, etc.;
• Solid maths foundation, including probability statistics, numerical optimization, etc., sensitive to data, good at discovering, analyzing and solving problems from data;
• Familiar with at least one of Flink, Spark, Hive etc., with big data parallel processing experience;

Preferred Qualification:

• Experience in large‑scale recommend/advertising systems, risk control systems or LLM is preferred