Australia Job Openings
TikTok
Researcher - Large Language Models, Trust and Safety (Australia)
Sydney
August 29, 2024
Tik Tok is the leading destination for short-form mobile video. At Tik Tok, our mission is to inspire creativity and bring joy. Tik Tok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Tik Tok 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 Tik Tok, 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.
About the Team
Our Trust and Safety RD team is fast growing and responsible for building machine learning models and systems to identify and defend internet abuse and fraud on our platform. Our mission is to protect billions of users and publishers across the globe every day. We embrace state-of-the-art machine learning technologies and scale them to detect and improve the tremendous amount of data generated on the platform. With the continuous efforts from our team, Tik Tok is able to provide the best user experience and bring joy to everyone in the world.
We are looking for researchers in the Large Language Model (LLM) domain who are going to conduct research on single modality and multi modality LLM pretraining and applications including in-context learning (ICL), supervised fine-tuning (SFT) and reinforcement learning based alignment. We are looking forward to applying LLM in trust and safety business scenarios so that we can protect our users and creators with the best moderation quality and cost efficiency. There are no doubt a lot of unsolved problems in the LLM domain which could have a huge impact on industry and academia. In the Trust & Safety team, we have real applications, resources and patience for technology incubation.
Your main responsibilities will be
- Lead the incubation of next-generation, high-capacity LLM solutions for the Trust & Safety business
- Identify research problems and dive deep for innovative solutions
- Work closely with cross-functional teams to plan and implement projects harnessing LLMs for diverse purposes and vertical domains
- Extend the insights and impact from industry to academia
Minimum Qualifications
- Ph.D in Computer Science, Data Science, Artificial Intelligence, or a related field
- Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, active learning, alignment research, agent ecosystem, etc.) and possess practical expertise in effectively implementing these advanced systems as a plus
- Proficiency in programming languages such as Python, Rust, or C++ and a track record of working with deep learning frameworks (e.g., pytorch, deepspeed, megatron, vllm, etc.).
- Strong understanding of distributed computing framework & performance tuning and verification for training/finetuning/inference; Being familiar with PEFT, RL, Mo E, Co T or Langchain is a plus.
- Excellent problem-solving skills and a creative mindset to address complex AI challenges. Demonstrated ability to drive research projects from idea to implementation, producing tangible outcomes.
- Published research papers or contributions to the LLM community would be a significant plus.
- Experience with inference tuning and Inference acceleration. Have a deep understanding of GPU and/or other AI accelerators, experience with large scale AI networks, pytorch 2.0 and similar technologies.
- Experience with evaluation of AI systems, LLM application & agent development is desirable.
In the spirit of reconciliation, Tik Tok acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their Elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
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