Machine Learning Engineer Graduate (Monetization GenAI)

Machine Learning Engineer Graduate (Monetization GenAI) - 2026 Start (BS/MS)

New Today

We are Generative AI team under Monetization Technology. Our team focuses on developing cutting-edge Generative AI techs across all modalities, including text, image, videos, landing pages, etc., and creates industry-leading technical solutions to improve creative efficiency for advertisers, agencies and creators. We are committed to automated creative workflows by leveraging Generative AI technologies, to increase overall revenue for advertisers, agencies and creators. We aim to drive and lead the generative AI in the ads tech and creative industry, powering products and driving values for our clients, creators, and the whole ecosystem. We are looking for infrastructure engineers who are excited to grow their 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 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. 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 resumes. Applications will be reviewed on a rolling basis. We encourage you to apply early. Responsibilities 1. Lead research in advancing technology in large language model or multimodality generative model architectures; 2. Research, implement and evaluate novel machine learning algorithms on generative models; 3. Collaborate with applied machine learning teams and infrastructure teams to ship new generative models into ad production.

Minimum Qualifications: - BS/MS in computer science, machine learning, or similar fields - Hands-on experience of developing multimodality foundation models and work or internship experience in an AI research organization is a plus - Strong publications record in top conferences or journals (., NeurIPS, ICML, ICLR, CVPR, etc) By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https:///legal/privacy

Apply

Location:: San Jose

Start a New Search