Research Engineer Intern (Agentic Systems & AI Infrastructure - TikTok-Generalized Arch) - 2027 Start (PhD)
TikTokSan Jose, California, United StatesInternshipEntry-levelPosted Today
TikTok is an international short video platform available in over 150 countries and regions, where we aim to inspire creativity and bring joy by helping people discover authentic and interesting moments. TikTok has offices around the world, with global headquarters in Los Angeles and Singapore, and additional offices in New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo, among others.
The TikTok Agentic Arch team is building AI-native engineering infrastructure that transforms how software is designed, built, and operated at TikTok scale. We research and deploy reliable long-horizon agents that can reason over large codebases, interact with complex tools and environments, and complete consequential engineering work across distributed production systems.
Our environment provides a unique opportunity to advance agent research through real-world execution feedback. You will develop frontier methods, evaluate them rigorously, and bring them into production through platforms used at large scale—creating measurable improvements in engineering productivity, software quality, and operational effectiveness.
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).
Responsibilities:
- Currently pursuing or recently completed a PhD in Computer Science or a related field, with relevant work in machine learning, natural language processing, software engineering, distributed systems, programming languages, or a related area.
- Demonstrated research or engineering experience in AI agents or closely related areas such as large language model reasoning, reinforcement learning, program synthesis, or AI for code.
- Strong understanding of one or more relevant areas, including agent planning and reasoning, model post-training, reinforcement learning, memory and context systems, tool learning, multi-agent systems, or agent evaluation.
- Strong programming and systems-building ability in at least one language such as Python, C++, Go, or Java, with the ability to turn research ideas into robust implementations.
- Ability to formulate ambiguous real-world problems, design rigorous experiments and evaluations, analyze results, and iterate from evidence.
- Strong communication and collaboration skills, with the ability to work across research, infrastructure, platform, and product teams.
Minimum Qualifications:
- Currently pursuing or recently completed a PhD in Computer Science or a related field, with relevant work in machine learning, natural language processing, software engineering, distributed systems, programming languages, or a related area.
- Demonstrated research or engineering experience in AI agents or closely related areas such as large language model reasoning, reinforcement learning, program synthesis, or AI for code.
- Strong understanding of one or more relevant areas, including agent planning and reasoning, model post-training, reinforcement learning, memory and context systems, tool learning, multi-agent systems, or agent evaluation.
- Strong programming and systems-building ability in at least one language such as Python, C++, Go, or Java, with the ability to turn research ideas into robust implementations.
- Ability to formulate ambiguous real-world problems, design rigorous experiments and evaluations, analyze results, and iterate from evidence.
- Strong communication and collaboration skills, with the ability to work across research, infrastructure, platform, and product teams.
Preferred Qualifications:
- Evidence of research excellence through influential publications, open-source work, deployed systems, or other significant contributions. Relevant venues include NeurIPS, ICML, ICLR, ACL, MLSys, OSDI, SOSP, NSDI, ICSE, and FSE.
- Experience building or deploying LLM agents, AI developer tools, or agent platforms in complex or large-scale environments.
- Hands-on experience with model post-training, reinforcement learning, execution-feedback loops, tool-using agents, distributed agent runtimes, or scalable evaluation systems.
- Experience working with large codebases, distributed systems, CI/CD and testing infrastructure, developer platforms, or production operations.
- A track record of translating research into measurable production impact.
As a condition of employment, all successful candidates must be able to establish authorization to work in the United States. For this position, the Company does not provide sponsorship or any immigration-related benefits.
By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy
The TikTok Agentic Arch team is building AI-native engineering infrastructure that transforms how software is designed, built, and operated at TikTok scale. We research and deploy reliable long-horizon agents that can reason over large codebases, interact with complex tools and environments, and complete consequential engineering work across distributed production systems.
Our environment provides a unique opportunity to advance agent research through real-world execution feedback. You will develop frontier methods, evaluate them rigorously, and bring them into production through platforms used at large scale—creating measurable improvements in engineering productivity, software quality, and operational effectiveness.
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).
Responsibilities:
- Currently pursuing or recently completed a PhD in Computer Science or a related field, with relevant work in machine learning, natural language processing, software engineering, distributed systems, programming languages, or a related area.
- Demonstrated research or engineering experience in AI agents or closely related areas such as large language model reasoning, reinforcement learning, program synthesis, or AI for code.
- Strong understanding of one or more relevant areas, including agent planning and reasoning, model post-training, reinforcement learning, memory and context systems, tool learning, multi-agent systems, or agent evaluation.
- Strong programming and systems-building ability in at least one language such as Python, C++, Go, or Java, with the ability to turn research ideas into robust implementations.
- Ability to formulate ambiguous real-world problems, design rigorous experiments and evaluations, analyze results, and iterate from evidence.
- Strong communication and collaboration skills, with the ability to work across research, infrastructure, platform, and product teams.
Minimum Qualifications:
- Currently pursuing or recently completed a PhD in Computer Science or a related field, with relevant work in machine learning, natural language processing, software engineering, distributed systems, programming languages, or a related area.
- Demonstrated research or engineering experience in AI agents or closely related areas such as large language model reasoning, reinforcement learning, program synthesis, or AI for code.
- Strong understanding of one or more relevant areas, including agent planning and reasoning, model post-training, reinforcement learning, memory and context systems, tool learning, multi-agent systems, or agent evaluation.
- Strong programming and systems-building ability in at least one language such as Python, C++, Go, or Java, with the ability to turn research ideas into robust implementations.
- Ability to formulate ambiguous real-world problems, design rigorous experiments and evaluations, analyze results, and iterate from evidence.
- Strong communication and collaboration skills, with the ability to work across research, infrastructure, platform, and product teams.
Preferred Qualifications:
- Evidence of research excellence through influential publications, open-source work, deployed systems, or other significant contributions. Relevant venues include NeurIPS, ICML, ICLR, ACL, MLSys, OSDI, SOSP, NSDI, ICSE, and FSE.
- Experience building or deploying LLM agents, AI developer tools, or agent platforms in complex or large-scale environments.
- Hands-on experience with model post-training, reinforcement learning, execution-feedback loops, tool-using agents, distributed agent runtimes, or scalable evaluation systems.
- Experience working with large codebases, distributed systems, CI/CD and testing infrastructure, developer platforms, or production operations.
- A track record of translating research into measurable production impact.
As a condition of employment, all successful candidates must be able to establish authorization to work in the United States. For this position, the Company does not provide sponsorship or any immigration-related benefits.
By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy