Machine Learning Engineer, AI Agent

Responsibilities

Our team focuses on the R&D of algorithm for TikTok international advertising customer growth. We leverage deep learning and large language model technologies to build an algorithmic system for advertiser acquisition and retention, optimize the operational efficiency of the international commerce platform, and empower the business to achieve sustainable long-term revenue growth.

What You'll Do
- Build the core "brain" of an AI agent for the advertising sales domain and track cutting-edge technologies. Explore mainstream Agent frameworks, continuously monitor the latest advancements in the AI Agent field, and introduce and validate the feasibility of new technologies-with a focus on enhancing automated task planning and scheduling, tool invocation, multimodal interaction, and deep research capabilities. Establish an Agent evaluation mechanism for Harness-driven iteration.
- Develop a Skills toolset for advertising sales and customer acquisition scenarios, building and optimizing a suite of high-performance, reusable Skills.
- Explore Agent automation and self-evolution, enabling the Agent to learn from real-world interaction data and continuously improve its decision-making and execution capabilities.
- Build stable and reliable Agent infrastructure, including performance and stability optimization of the Agent system.

Qualifications

Minimum Qualifications:
- Master's degree or higher in Computer Science, Artificial Intelligence, Natural Language Processing, or related fields.
- 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. Practical experience in fine-tuning model capabilities for specific tasks is preferred.
- Excellent coding skills with strong fundamentals in data structures and algorithms. Proficiency in C/C++ or Python.
- Strong teamwork, collaboration, and communication skills.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $387600 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

Our team focuses on the R&D of algorithm for TikTok international advertising customer growth. We leverage deep learning and large language model technologies to build an algorithmic system for advertiser acquisition and retention, optimize the operational efficiency of the international commerce platform, and empower the business to achieve sustainable long-term revenue growth.

What You'll Do
- Build the core "brain" of an AI agent for the advertising sales domain and track cutting-edge technologies. Explore mainstream Agent frameworks, continuously monitor the latest advancements in the AI Agent field, and introduce and validate the feasibility of new technologies-with a focus on enhancing automated task planning and scheduling, tool invocation, multimodal interaction, and deep research capabilities. Establish an Agent evaluation mechanism for Harness-driven iteration.
- Develop a Skills toolset for advertising sales and customer acquisition scenarios, building and optimizing a suite of high-performance, reusable Skills.
- Explore Agent automation and self-evolution, enabling the Agent to learn from real-world interaction data and continuously improve its decision-making and execution capabilities.
- Build stable and reliable Agent infrastructure, including performance and stability optimization of the Agent system.

Qualifications

Qualifications

Minimum Qualifications:
- Master's degree or higher in Computer Science, Artificial Intelligence, Natural Language Processing, or related fields.
- 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. Practical experience in fine-tuning model capabilities for specific tasks is preferred.
- Excellent coding skills with strong fundamentals in data structures and algorithms. Proficiency in C/C++ or Python.
- Strong teamwork, collaboration, and communication skills.