CPT Applied Scientist Jobs
Applied Scientist roles sit at the intersection of research and production systems, making them a strong CPT fit for graduate students in computer science, statistics, or data science. Your DSO must authorize CPT before you start, and the work must connect directly to your degree program's learning objectives.
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Get Access To All JobsINTRODUCTION
Applied Scientist Intern - Trust and Safety (Multimodal Foundation Model) - Global Frontier Tech Recruitment Program - 2027 Start (PhD)
LOCATION
Location: San Jose
EMPLOYMENT TYPE
Employment Type: Intern
JOB CODE
Job Code: A219452
Responsibilities
We are looking for talented individuals to join our team in 2027. As an intern, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.
Successful candidates must be able to commit to an onboarding during the summer 2027. Please state your availability clearly in your resume.
ABOUT THE TEAM
Our Trust and Safety team is fast growing and responsible for building machine learning models and systems to protect our users from the impact of negative content. Our mission is to protect billions of users and publishers across the globe every day. We embrace state-of-the-art machine learning technologies and scale them to moderate the tremendous amount of data generated on the platform. With our team's continuous efforts, TikTok can provide the best user experience and bring joy to everyone in the world.
PROJECT OVERVIEW, CHALLENGES & VALUE
With the rapid development of AIGC and the globalization of content ecosystems, content moderation faces three major challenges: evolving policies, surging complexity in multilingual and multimodal content, and upgraded generative adversarial attacks. The traditional "perception → classification" paradigm has reached its limit. This topic focuses on two frontier directions:
-
Multimodal moderation foundation model: We study large-scale MoE architecture training and routing optimization, cross-modal alignment and reasoning for multimodality (text/image/video/audio), Unified Understanding & Generation, and high-quality synthetic data generation for moderation scenarios (self-play / adversarial augmentation).
-
Agentic moderation system: Drawing on advanced agent learning paradigms, it uses reinforcement learning to enhance the agent’s multi-step decision-making capabilities. It dynamically builds moderation context and integrates a flexible tool ecosystem, enabling autonomous planning, tool collaboration, and interpretable closed-loop reasoning. This drives a paradigm shift from passive classification to proactive intelligent decision-making in moderation.
Key challenges include:
1. MoE-based multimodal safety foundation model: training stability and routing optimization for large-scale sparse MoE, cross-modal token alignment, and unified architecture design for understanding and generation
2. RL-driven agentic decision-making: end-to-end training of agent multi-step reasoning and tool-call strategies based on GRPO/PPO, overcoming bottlenecks in sample efficiency and training stability
3. Context engineering and tool collaboration: dynamic context assembly, MCP-based tool ecosystem construction, multi-source heterogeneous evidence fusion, and GraphRAG strategy retrieval
4. Generalization and adversarial robustness: generalization across 200+ languages/strategies, adversarial detection of AIGC content, and design of multi-dimensional reward signals for few-shot scenarios
Project Value:
1. Technological leadership: The integration of RL, Agentic, and multimodal foundation models represents the frontier of AI today. This topic pioneers their application to large-scale content moderation scenarios, with unique advantages in data volume and real-world feedback loops that are impossible to reproduce in pure academic settings.
2. Business value: Serving content safety for billions of users globally and driving the evolution of moderation from dependence on humans and external APIs towards fully automated agentic moderation. This can directly reduce costs by hundreds of millions of US dollars while improving moderation consistency and response speed.
3. Industry leadership: Mature RL-driven agentic moderation systems do not yet exist in the industry. This topic could hopefully define the technological paradigm for this direction and produce research outcomes with significant industry influence.
MINIMUM QUALIFICATIONS
- Currently pursuing a PhD in Computer Science, Data Science, Artificial Intelligence, or a related field
- Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, alignment research, agent ecosystem, etc.) and possess practical expertise in effectively implementing these advanced systems as a plus
- Proficiency in programming languages such as Python, Rust, or C++ and a track record of working with deep learning frameworks (e.g., pytorch, deepspeed, megatron, vllm, etc.)
- Strong understanding of distributed computing framework & performance tuning and verification for training/finetuning/inference; Being familiar with PEFT, RL, MoE, CoT or Langchain is a plus
PREFERRED QUALIFICATIONS
- Excellent problem-solving skills and a creative mindset to address complex AI challenges. Demonstrated ability to drive research projects from idea to implementation, producing tangible outcomes.
- Published research papers or contributions to the LLM community would be a significant plus.
- Experience with inference tuning and Inference acceleration. Have a deep understanding of GPU and/or other AI accelerators, experience with large scale AI networks, pytorch 2.0 and similar technologies.
- Experience with evaluation of AI systems, LLM application & agent development is desirable.
JOB INFORMATION
【For Pay Transparency】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) 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.
ABOUT TIKTOK
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
WHY JOIN US
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
DIVERSITY & INCLUSION
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TIKTOK ACCOMMODATION
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request
INTRODUCTION
Applied Scientist Intern - Trust and Safety (Multimodal Foundation Model) - Global Frontier Tech Recruitment Program - 2027 Start (PhD)
LOCATION
Location: San Jose
EMPLOYMENT TYPE
Employment Type: Intern
JOB CODE
Job Code: A219452
Responsibilities
We are looking for talented individuals to join our team in 2027. As an intern, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.
Successful candidates must be able to commit to an onboarding during the summer 2027. Please state your availability clearly in your resume.
ABOUT THE TEAM
Our Trust and Safety team is fast growing and responsible for building machine learning models and systems to protect our users from the impact of negative content. Our mission is to protect billions of users and publishers across the globe every day. We embrace state-of-the-art machine learning technologies and scale them to moderate the tremendous amount of data generated on the platform. With our team's continuous efforts, TikTok can provide the best user experience and bring joy to everyone in the world.
PROJECT OVERVIEW, CHALLENGES & VALUE
With the rapid development of AIGC and the globalization of content ecosystems, content moderation faces three major challenges: evolving policies, surging complexity in multilingual and multimodal content, and upgraded generative adversarial attacks. The traditional "perception → classification" paradigm has reached its limit. This topic focuses on two frontier directions:
-
Multimodal moderation foundation model: We study large-scale MoE architecture training and routing optimization, cross-modal alignment and reasoning for multimodality (text/image/video/audio), Unified Understanding & Generation, and high-quality synthetic data generation for moderation scenarios (self-play / adversarial augmentation).
-
Agentic moderation system: Drawing on advanced agent learning paradigms, it uses reinforcement learning to enhance the agent’s multi-step decision-making capabilities. It dynamically builds moderation context and integrates a flexible tool ecosystem, enabling autonomous planning, tool collaboration, and interpretable closed-loop reasoning. This drives a paradigm shift from passive classification to proactive intelligent decision-making in moderation.
Key challenges include:
1. MoE-based multimodal safety foundation model: training stability and routing optimization for large-scale sparse MoE, cross-modal token alignment, and unified architecture design for understanding and generation
2. RL-driven agentic decision-making: end-to-end training of agent multi-step reasoning and tool-call strategies based on GRPO/PPO, overcoming bottlenecks in sample efficiency and training stability
3. Context engineering and tool collaboration: dynamic context assembly, MCP-based tool ecosystem construction, multi-source heterogeneous evidence fusion, and GraphRAG strategy retrieval
4. Generalization and adversarial robustness: generalization across 200+ languages/strategies, adversarial detection of AIGC content, and design of multi-dimensional reward signals for few-shot scenarios
Project Value:
1. Technological leadership: The integration of RL, Agentic, and multimodal foundation models represents the frontier of AI today. This topic pioneers their application to large-scale content moderation scenarios, with unique advantages in data volume and real-world feedback loops that are impossible to reproduce in pure academic settings.
2. Business value: Serving content safety for billions of users globally and driving the evolution of moderation from dependence on humans and external APIs towards fully automated agentic moderation. This can directly reduce costs by hundreds of millions of US dollars while improving moderation consistency and response speed.
3. Industry leadership: Mature RL-driven agentic moderation systems do not yet exist in the industry. This topic could hopefully define the technological paradigm for this direction and produce research outcomes with significant industry influence.
MINIMUM QUALIFICATIONS
- Currently pursuing a PhD in Computer Science, Data Science, Artificial Intelligence, or a related field
- Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, alignment research, agent ecosystem, etc.) and possess practical expertise in effectively implementing these advanced systems as a plus
- Proficiency in programming languages such as Python, Rust, or C++ and a track record of working with deep learning frameworks (e.g., pytorch, deepspeed, megatron, vllm, etc.)
- Strong understanding of distributed computing framework & performance tuning and verification for training/finetuning/inference; Being familiar with PEFT, RL, MoE, CoT or Langchain is a plus
PREFERRED QUALIFICATIONS
- Excellent problem-solving skills and a creative mindset to address complex AI challenges. Demonstrated ability to drive research projects from idea to implementation, producing tangible outcomes.
- Published research papers or contributions to the LLM community would be a significant plus.
- Experience with inference tuning and Inference acceleration. Have a deep understanding of GPU and/or other AI accelerators, experience with large scale AI networks, pytorch 2.0 and similar technologies.
- Experience with evaluation of AI systems, LLM application & agent development is desirable.
JOB INFORMATION
【For Pay Transparency】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) 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.
ABOUT TIKTOK
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
WHY JOIN US
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
DIVERSITY & INCLUSION
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TIKTOK ACCOMMODATION
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request
See all CPT Applied Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new CPT Applied Scientist Jobs.
Get Access To All JobsApplied Scientist CPT: Frequently Asked Questions
Does an Applied Scientist role qualify for CPT authorization?
Yes, if the role is an integral part of your curriculum and your school offers a course or research requirement it can be tied to. Applied Scientist positions in machine learning, statistical modeling, or applied research typically map well to graduate programs in computer science, data science, or statistics. Your DSO makes the final call based on how the role connects to your specific degree plan.
Can I do full-time CPT as an Applied Scientist without affecting OPT eligibility?
You can, but full-time CPT for 12 months or more eliminates your OPT eligibility entirely. Most F-1 students in Applied Scientist roles structure CPT as part-time during the academic year or limit full-time CPT to one semester. Confirm your cumulative CPT duration with your DSO before accepting a full-time offer.
How do I find Applied Scientist employers who are familiar with CPT hiring?
Search Migrate Mate for Applied Scientist roles filtered by employers with documented LCA filing history. Employers who've filed LCAs for research or ML roles are more likely to have HR processes that accommodate CPT documentation requirements, including the offer letter language your DSO needs before authorizing your work.
What does my employer need to provide for CPT authorization?
Your employer must provide a written offer letter that includes the job title, start and end dates, whether the position is full-time or part-time, and the work location. Some DSOs also require a brief description of the role's duties. Your employer doesn't file anything with USCIS for CPT, but their letter is what your DSO uses to update your I-20.
Does CPT work as an Applied Scientist count toward H-1B specialty occupation evidence?
Yes. CPT employment in an Applied Scientist role can strengthen an H-1B visa petition by documenting U.S. work history in a specialty occupation. Keeping records of your projects, the technical skills applied, and how they connect to your degree helps your employer's attorney build the specialty occupation argument when filing Form I-129 later.