San Jose, California, United StatesFull TimeEntry-levelPosted Today
The Commercial AI-CRM and Transaction team focuses on TikTok advertiser growth algorithms. Leveraging deep learning and large language model technologies, the team builds an algorithmic system for advertiser growth, optimizes the operational efficiency of global commercial platforms, and empowers sustainable long-term business revenue growth.
The team is exploring a new paradigm of enterprise intelligence in the era of large models, building next-generation intelligent Agent systems for customer growth, sales operations, and business decision-making. The team is committed to the innovative application of LLM, Agent, multimodal intelligence, and machine learning technologies in real-world business scenarios, driving the evolution of AI from an “assistant tool” into an intelligent partner capable of understanding business, developing strategies, and executing tasks.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities:
- Explore Enterprise-level Intelligent Agent Technologies: Research LLM Agent technologies, including complex reasoning, task planning, knowledge augmentation, long-term memory, and autonomous decision-making. Build intelligent systems capable of understanding business objectives, completing complex tasks, and continuously optimizing.
- Intelligent Dialogue and AI Call Technologies: Explore next-generation intelligent interaction technologies, including real-time speech, multi-turn dialogue, intent understanding, and dialogue strategy generation. Build AI Sales Agents with natural communication capabilities to improve customer engagement and conversion efficiency.
- Intelligent Decision-Making and Risk Management: Combine customer data, business knowledge, and machine learning models to explore customer risk identification, credit limit estimation, and intelligent decision-making capabilities. Help businesses achieve a balance between growth and risk management.
- Intelligent Customer Understanding and Business Insights: Leverage LLM and machine learning technologies to understand customer industries, brands, business status, and organizational relationships. Build intelligent customer profiles, identify customer needs and potential business opportunities, and enhance customer management capabilities.
Minimum Qualifications:
- Individuals who are completing or have recently completed a Master's degree in Computer Science, Artificial Intelligence, Natural Language Processing, or a related technical discipline.
- Familiarity with at least one mainstream Agent framework (e.g., LangGraph, OpenClaw, Hermes, Codex, Claude Code, etc.) with hands-on experience.
- Deep understanding of the core principles of Large Language Models (LLMs) and AI Agents. Familiarity with mainstream Agent architectures (e.g., ReAct/PlanAct), Multi-Agent systems, and concepts such as Context Engineering and Memory.
- Solid AI/ML background with in-depth knowledge of post-training techniques such as SFT and RLHF.
- Excellent coding skills with strong fundamentals in data structures and algorithms. Proficiency in C/C++ or Python.
- Strong teamwork, collaboration, and communication skills.
Preferred Qualifications:
- Practical experience in fine-tuning model capabilities for specific tasks is preferred.
The team is exploring a new paradigm of enterprise intelligence in the era of large models, building next-generation intelligent Agent systems for customer growth, sales operations, and business decision-making. The team is committed to the innovative application of LLM, Agent, multimodal intelligence, and machine learning technologies in real-world business scenarios, driving the evolution of AI from an “assistant tool” into an intelligent partner capable of understanding business, developing strategies, and executing tasks.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities:
- Explore Enterprise-level Intelligent Agent Technologies: Research LLM Agent technologies, including complex reasoning, task planning, knowledge augmentation, long-term memory, and autonomous decision-making. Build intelligent systems capable of understanding business objectives, completing complex tasks, and continuously optimizing.
- Intelligent Dialogue and AI Call Technologies: Explore next-generation intelligent interaction technologies, including real-time speech, multi-turn dialogue, intent understanding, and dialogue strategy generation. Build AI Sales Agents with natural communication capabilities to improve customer engagement and conversion efficiency.
- Intelligent Decision-Making and Risk Management: Combine customer data, business knowledge, and machine learning models to explore customer risk identification, credit limit estimation, and intelligent decision-making capabilities. Help businesses achieve a balance between growth and risk management.
- Intelligent Customer Understanding and Business Insights: Leverage LLM and machine learning technologies to understand customer industries, brands, business status, and organizational relationships. Build intelligent customer profiles, identify customer needs and potential business opportunities, and enhance customer management capabilities.
Minimum Qualifications:
- Individuals who are completing or have recently completed a Master's degree in Computer Science, Artificial Intelligence, Natural Language Processing, or a related technical discipline.
- Familiarity with at least one mainstream Agent framework (e.g., LangGraph, OpenClaw, Hermes, Codex, Claude Code, etc.) with hands-on experience.
- Deep understanding of the core principles of Large Language Models (LLMs) and AI Agents. Familiarity with mainstream Agent architectures (e.g., ReAct/PlanAct), Multi-Agent systems, and concepts such as Context Engineering and Memory.
- Solid AI/ML background with in-depth knowledge of post-training techniques such as SFT and RLHF.
- Excellent coding skills with strong fundamentals in data structures and algorithms. Proficiency in C/C++ or Python.
- Strong teamwork, collaboration, and communication skills.
Preferred Qualifications:
- Practical experience in fine-tuning model capabilities for specific tasks is preferred.