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Open nowPosted today

Software Engineer in Machine Learning Infra, TikTok Recommendation Architecture

MyCareersFuture90,627 open roles

Pay
SGD 6,500 – SGD 13,000 a month
Where
Central, Singapore
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Your applicationOpen nowSoftware Engineer in Machine Learning Infra, TikTok Recommendation ArchitectureMyCareersFuture · Central, Singapore
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  2. 4.0%3 days
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  5. 34.1%30 days
This job: posted today

MyCareersFuture median: 7 days open

The posting

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

TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.

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 TikTok users. The team is responsible for system stability and high availability, online services and offline data flow performance optimization, solving system bottlenecks, reducing cost overhead, building data and service mid-platform, realizing flexible and scalable high-performance storage and computing systems.

Responsibilities

- Serving and training infra optimization of machine learning models

- Build and maintain high performance online services for TikTok recommendation system

- Build globalized large-scale recommendation system

- Research, design, and develop computer and network software or specialised utility programs

- Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis

- Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures

- Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements

Qualifications

Minimum Qualification(s)

- Bachelor's degree or above, majoring in Computer Science, or related fields, with experience building scalable systems.

- Experience at least one or two programming languages in Linux environment such as C/C++/golang;

- Understand GPU hardware architecture, understand GPU software stack (CUDA, cuDNN), and have experience in GPU performance analysis;

Preferred Qualification(s)

- Have experience in deep model inference/training, debugging, tuning, and familiar with model optimization tools such as TVM, MLIR, XLA;

- Familiar with mainstream machine learning frameworks (e.g., Tensorflow, Pytorch, MxNet);

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