Algorithm Engineer, E-Commerce Governance and Experience - USDS

In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.

Responsibilities:
- Develop LLM-based CCR/VOC Models: Design and implement LLM-based CCR/VOC models, to cover user feedback from multiple channels, including reviews, after-sales service, customer service conversations, and tNPS, etc. Based on a 100+ intent classification system, identifies the user's feedback intent accurately.
- Apply Advanced LLM Techniques: Utilize state-of-the-art LLM post-training techniques, such as instruction tuning, Reinforcement Learning from Human Feedback (RLHF), and continuous learning, to optimize the system with minimal labeled data.
- Build Robust Training Datasets: Identify challenging user feedback scenarios-including logistics inquiries, merchant issues, and platform-related problems-and construct specialized datasets to enhance AI model training.
- Enable Multilingual and Multicultural Support: Build AI models capable of recognizing user feedback across diverse languages and cultural backgrounds, ensuring accurate semantic understanding for a global audience.
- Optimize Model Efficiency and Deployment: Research and apply model compression, quantization, and efficient inference techniques to ensure the AI assistant operates at scale with low latency and high reliability.
- CCR/VOC RCA Agents: Focusing on pain points in CCR, such as the need for rapid implementation of new labels and inefficient CCR problem handling processes in business side, this project leverages the agent's autonomous interaction and intelligent decision-making capabilities to optimize existing models and processes. Through scenario-based training and iteration, the agent becomes a highly efficient assistant for CCR operations, solving the problems of slow response and low conversion rates in traditional models, and improving service quality and customer experience.

Qualifications

Minimum Qualifications:
- Bachelor's degree in Computer Science or a related technical field.
- 2+ years of professional experience in one or more of the following fields: Machine Learning, Natural Language Processing (NLP), or Computer Vision.
- Proficiency in software development with at least one of the following programming languages: C++, Python, Go, or Java.

Preferred Qualifications:
- LLM Development & Post-Training: Experience in fine-tuning, distillation, or reinforcement learning for large language models in conversational AI applications.
- Multilingual AI Development: Proficiency in multilingual NLP, machine translation, and cross-lingual dialogue modeling.
- CV/Multimodal Large Model Development: Experience in developing and optimizing e-commerce video and product multimodal large models, combining LLMs with video/product representations to support tasks like multimodal classification, video QA, and cross-modal retrieval.
- E-commerce Business Acumen: A strong understanding of e-commerce policies, dispute resolution workflows, and merchant-buyer interactions to inform AI service design.
- Advanced NLP & Deep Learning: Expertise in AI agents, Retrieval-Augmented Generation (RAG), Mixture of Experts (MoE), sparse attention, reinforcement learning, and inference-time scaling.
- Scalability & Efficiency: Experience with distributed model training, low-latency inference, and deploying models efficiently.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $136800 - $359720 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.

Client-provided location(s): San Jose, CA

Job ID: TikTok-7579754366782376245

Employment Type: OTHER

Posted: 2025-12-04T20:28:41