
Machine Learning Engineer , E-commerce Merchant Growth (LLM & Agentic Systems)
Job Description
About Our Team Join the E-commerce Merchant Growth team at TikTok! We’re the core team building LLM-powered agentic systems that drive and accelerate seller growth across global markets. We bring cutting-edge AI into production at scale — from applied LLMs and multi-agent systems to real-world business impact in one of the fastest-growing e-commerce ecosystems in the world. We’re looking for brilliant and motivated ML engineers eager to apply their knowledge in machine learning (ML), operations research (OR), data mining, and large-scale intelligent systems to real-world challenges. If you love building, experimenting, and shaping how AI transforms commerce, we want to talk to you. Applications are reviewed on a rolling basis — we encourage you to apply early.
Responsibilities:
- Develop and deploy deep learning and LLM-powered systems for merchant operational tools and global e-commerce growth scenarios.
- Leverage large-scale e-commerce data to power agentic systems that generate actionable insights — from CRM content generation and store decoration to automated email reply and outreach optimization.
- Use ML models to predict seller performance, identify growth gaps, and provide agent-based recommendations (e.g., campaign design, pricing, and promotions).
- Collaborate with cross-functional partners (product, data science, operations) to design and deliver 0-to-1 projects that fundamentally reshape how merchants grow, impacting millions of daily sales across key categories (beauty, fashion, health, etc.).
- Build lead-scoring models, merchant tiering algorithms, outreach optimization systems, and knowledge graphs to enhance onboarding and retention efficiency.
- Apply data mining and predictive modeling to optimize product pricing, promotion, and traffic allocation strategies.
- Communicate technical insights effectively to both technical and non-technical stakeholders, fostering a collaborative, data-driven culture.
Minimum Qualifications:
- Bachelor degree and above in Computer Science, Artificial Intelligence, Statistics, Operations Research, or related fields, with experience in data mining or deep learning.
- Solid understanding of ML and deep learning fundamentals — classification, regression, NLP, and model optimization.
- Strong programming skills in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
- Demonstrated ability to connect algorithms with business impact; highly self-driven with strong ownership and curiosity.
- 2+ years of experience as an ML Engineer, ideally in NLP, recommendation, marketing, or growth algorithms.
- Excellent analytical, teamwork, and communication skills.
Preferred Qualifications:
- Experience in applied LLMs, multi-agent systems, or RAG (retrieval-augmented generation) pipelines.
- Published work in top-tier conferences (KDD, NeurIPS, ICML, SIGIR, WSDM, WWW, AAAI, IJCAI, RecSys, etc.) or success in ML competitions.
- Hands-on experience in e-commerce or other large-scale, data-intensive production environments.
- Passion for building agentic systems that drive real-world business outcomes.