Research Intern; AML-Algorithm PhD
Listed on 2026-10-11
-
Software Development
Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software)
Responsibilities
You will be joining our Applied Machine Learning team, a central team responsible for delivering state-of-the-art solutions powering our company's recommendations, ads, and search systems across various products such as Tik Tok, Douyin. We own the end-to-end ML lifecycle, from ideation and research to building, deploying, and iterating on models in production. We are looking for candidates who are passionate about solving complex problems and have a strong foundation in machine learning theory and practice.
ResponsibilitiesYou will be joining our Applied Machine Learning team, a central team responsible for delivering state-of-the-art solutions powering our company's recommendations, ads, and search systems across various products such as Tik Tok, Douyin. We own the end-to-end ML lifecycle, from ideation and research to building, deploying, and iterating on models in production. We are looking for candidates who are passionate about solving complex problems and have a strong foundation in machine learning theory and practice.
Responsibilities- Conduct research in machine learning for recommendation systems, with opportunities to explore large-scale recommendation models, generative recommendation, or reinforcement learning for personalization.
- Explore and prototype new modeling strategies that leverage multi-modal data (e.g., text, image, video) to enhance content and user understanding.
- Investigate long-term user behavior modeling and reinforcement learning techniques to improve sustained engagement.
- Collaborate with mentors and other researchers/engineers to test your ideas in real-world environments.
- Share findings through internal presentations, technical reports, and potentially external publications.
Minimum Qualifications:
- Currently pursuing a Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
- Strong research background in machine learning, deep learning, recommender systems, or related areas.
- Proficiency in at least one programming language such as Python or C++, and familiarity with deep learning frameworks (e.g., PyTorch, Tensor Flow).
- Solid understanding of modern machine learning methods, such as transformers, large language models (LLMs), or multi-modal learning.
- Demonstrated ability to conduct independent research, with strong problem-solving and analytical skills.
- Prior research or publications in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD, Rec Sys, WWW).
- Experience with large-scale ML systems or end-to-end ML pipelines is a plus.
- Passion for applying research to real-world challenges in recommendation, personalization, and user experience.
Compensation description (Hourly) - Campus Intern
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) CandidatesQualified 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…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).