Machine Learning Engineer Graduate (Commercial AI-CRM and Transaction) - 2027 Start

Responsibilities

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.

Qualifications

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.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $128000 - $256000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

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:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

Responsibilities

Responsibilities

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.

Qualifications

Qualifications

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.