Machine Learning Engineer Intern (E-Commerce Recommendation Foundation) - 2027 Start (PhD) San [...]
$60 per hourTikTok
Discover a career that energizes and excites you every day. @2026 TikTok Technology Location: San Jose Employment Type: Intern Job Code:
A229465
Share this listing: Responsibilities The Recommendation Foundation team within TikTok’s Data – Global E-commerce organization is dedicated to building shared Recommendation Foundation Models across scenarios. We are exploring an event-sequence-driven generative recommendation paradigm that deeply integrates large language and vision-language models (LLMs/VLMs), multimodal understanding, reinforcement learning, and system optimization, advancing recommendation systems beyond click prediction toward general-purpose recommendation agents.We believe the future of recommendation is not only about predicting clicks, but about understanding the relationships between people and content and generating new connections. We value original exploration and encourage research thinking and engineering practice equally. Every team member can propose hypotheses and validate ideas in an open environment; your code and publications may help shape the next generation of recommendation systems. We are looking for people with a general-intelligence mindset to redefine recommendation with us.We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date). Qualifications Minimum Qualifications Currently pursuing a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics or a related discipline. Solid foundation in machine learning and deep learning, with strong interest in LLMs and generative recommendation. Proficiency in Python and experience with deep learning frameworks such as PyTorch. Self-driven, with a strong research mindset and solid engineering skills. Preferred Qualifications Experience with pre-training, mid-training, or post-training of LLMs or Foundation Models. Research or project experience in generative recommendation, LLM-native recommendation, or multimodal semantic tokenization. Publications on LLM-related topics at top-tier machine learning or natural language processing conferences, such as NeurIPS, ICML, ICLR, ACL, EMNLP, or NAACL, or strong achievements in major technical competitions. Job Information The hourly rate range for this position in the selected city is $60- $60. Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance. The Company reserves the right to modify or change these benefits programs at any time, with or without notice. For Los Angeles County (unincorporated) Candidates: Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:- Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
- Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
- Exercising sound judgment.
Vacancy posted 2 days ago
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