Machine Learning Engineer Graduate (Monetization Technology - GenAI , Ads Creative & Ecosystem) - 2026 Start (BS/MS)

A "creative" is the ad (in the form of a short-form video) served to TikTok users, composed of video, background music, call-to-action card, post-click landing page, and other formats that get delivered to users. A quote goes "creativity is the soul of advertising", because a good ad creative is effective, yet difficult to produce, especially at the scale of TikTok advertising.

TikTok Ads Creative & Ecosystem team tackles the challenge of creating engaging and effective ad creatives at scale. Our mission is to build cutting-edge tech solutions for ad understanding, production, and optimization, empowering advertisers, creators, and partners to deliver the best creative experiences.

The team is building platforms to provide in-depth and unique AI-driven data insights to provide creative guidance to advertisers, which is the key for their ads planning and iteration. We are striving to focus on creative insights direction, grow business understanding, build highly scalable and reliable software/infrastructure, partner across functions with global teams, and make big impacts. If you are someone who welcomes challenges, we are eager to have you on the team!

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

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:
1. AI Image Generation and Editing Capability Iteration: Develop deep understanding of advertising creative requirements and market trends, leverage cutting-edge AIGC technologies and LLMs to continuously iterate and optimize image generation and editing functionalities, enhance advertising creative quality, and effectively improve ad performance and conversion rates.
2. Model Training and Fine-tuning: Lead end-to-end training processes for image generation models, including but not limited to post-training optimization and reinforcement learning fine-tuning, ensuring high-quality, accurate, and business-relevant model outputs through data-driven methodologies.
3. Data Management and Preprocessing: Manage comprehensive data preparation workflows including data collection, cleaning, validation, and preprocessing for model training pipelines, ensuring optimal data quality and integrity to support robust model performance and reliable training outcomes.
4. Technology Research and Implementation: Maintain expertise in the latest developments across multimodal and generative AI domains, proactively identifying and integrating breakthrough technologies to advance product capabilities and maintain competitive technological advantages.

Minimum Qualifications:
1. Final year or recent graduate with a background in - Computer Science, Artificial Intelligence, Mathematics, Electronic Information Engineering, possessing a comprehensive knowledge of advertising and creative technology.
2. Relevant experience in AI/ML model development, particularly in computer vision and image generation.
3. Exhibiting enthusiasm for AI and content creation, and having the capability to design AI solutions that are in line with business objectives.
4. Experience in deep learning frameworks (PyTorch, TensorFlow) and generative models (Diffusion Models, GANs, VAEs)


Preferred Qualifications:
1. Hands-on experience in model development and AI project deployment, with expertise in multimodal classification, retrieval, content matching, and video captioning.
2. Strong skills in creating high-quality content using LLM/MLLM/AIGC technologies.
3. Insight into the technical roadmap and trends in AI subfields like audio, image, video, and natural language processing. Preference for candidates with top-tier publications in relevant AI areas.
4. Proficiency in reinforcement learning and post-training optimization techniques.

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