Machine Learning Engineer - TikTok Business Integrity

Our Business Integrity team has a strong user focus and a dedication to technical excellence. We aim to meet our users' needs with reliable and high-performing platforms and services. We are looking for strong machine learning engineers who are excited to grow their business understanding, build highly scalable machine learning models, and partner across disciplines with global teams, in pursuit of excellence. Given the fast growth of TikTok in the world, we are working on building a next-generation content understanding system for TikTok monetization. We are seeking machine learning engineers at all levels experienced in machine learning, which can help us create an ecosystem that rewards high quality user experience and advertiser value.

Responsibilities

1. Be responsible for content understanding of commercial products, such as ads, e-commerce, short video, and live streaming.
2. Be responsible for data mining, feature engineering, and building scalable machine learning models to establish monetization ecology.
3. Optimize computational efficiency and improve stability of machine learning models to deal with billion scale business data.
4. Based on business data, explore and implement various cutting-edge technologies, such as pre-training, self-supervised learning, few-shot learning, etc.
5. Explore state-of-the-art AIGC techniques and build a new generation of AIGC-based monetization ecology systems.

Qualifications

1. Bachelor's degree or above, majoring in Computer Science, Computer Engineering, Electrical Engineering, or other related fields.
2. Have a solid foundation with common machine learning related techniques and algorithms (e.g. classification, clustering, regression, etc.). Be proficient with at least one deep learning framework (e.g. PyTorch,TensorFlow).
3. Related experience in at least one of the following areas
a. Be familiar with computer vision related tasks. Have rich experience in at least one aspect, such as image/video classification, object detection, image/video retrieval, OCR, image segmentation, etc.
b. Be familiar with NLP-related tasks. Have experience in at least one aspect, such as text classification, semantic analysis, sentiment analysis, NER, etc.
c. Be familiar with audio-related tasks. Have experience in at least one aspect, such as ASR, AED, LID, etc.
d. Be familiar with multimodal machine learning, large-scale multimodal pre-training, etc.
e. Be familiar with the theory and application of graph networks, knowledge graphs, and have relevant experience.
f. Be familiar with model acceleration techniques such as pruning, quantization, distillation, etc.; Have relevant experience in deploying models using frameworks such as TensorRT.
4. Solid programming foundation. Be familiar with basic data structures and algorithms.
5. Have excellent analytical and problem-solving skills, logical thinking skills, communication and collaboration skills. Maintain curiosity about new things, and have a strong sense of responsibility, integrity and reliability.
6. Having published papers in top AI conferences or journals (CVPR, ICCV, ECCV, TPAMI, IJCV, ICML, NeurIPS, ICLR, ACL, EMNLP, NAACL, etc.) is a plus.
7. Being familiar with generative models is a plus, such as GPT, Stable Diffusion, 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.

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at tt.accommodations@tiktok.com