Backend Engineer, Ark Large Model Platform - 2024 Start

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About the Team
The Applied Machine Learning (AML) - Enterprise team provides machine learning platform products on VolcanoEngine with cloud native resource scheduling system which intelligently orchestrates different tasks and jobs with minimised costs of every experiment and maximised resource utilisation, rich modelling tools including customised machine learning tasks and web IDE, and multi-framework high performance model inference services.

In 2021, through VolcanoEngine, we released this machine learning infrastructure to the public, to provide more enterprises with reduced costs of computation power, lower barriers to machine learning engineering and deeper developments in AI capabilities.

We are looking for talented individuals to join us in 2024. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities
Responsible for Ark Large Model Platform development on Volcano Engine, researching systematic solutions on large model solution implementations and applications in various industries, striving to reduce the IT cost of large model applications, meeting the users' ever-growing demand for intelligent interaction and improving the lifestyle and communications of users in the future world.

• 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

• Final year or recent graduate with a background in Software Development, Computer Science, Computer Engineering, Electrical Engineering or a related technical discipline.
• Familiar with developments and operations of distributed systems under Linux platform.
• Proficient with at least 2 or more programming languages such as Golang / Python / C / C++ / Java / Scala / Javascript. ACM ICPC / Codeforces winners are preferred
• Excellent in technical design and coding skills. Able to balance technical perspectives with product sense, hardware performance & stability and team cooperation.
• Experienced or interested in at least one of the following topics:

1. Machine Learning Application: had experience in developments or implementations in data, model training, inference, application in various machine learning domains such as LLM / CV / NLP / Speech / Recommendation / Risk Control, etc.
2. LLM Application: dataset construction (conversations, RLHF, etc.), high performance finetuning (LoRA / P-Tuning / RLHG), model inference and deployment, applications (prompt engineering, retrieval augmentation, LangChain), new model exploration (LLama / Falcon / miniGPT4)
3. Cloud Computing: kubernetes application development (such as Operator), micro-service & service mesh, flow control, cloud storage, exploration of technology commercialization, Terraform and etc.

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.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy.

If you have any questions, please reach out to us at [email protected].