Machine Learning Engineer - E-commerce Merchant Growth (LLM & Agentic Systems)

TikTok Inc.

San Jose (CA)

On-site

USD 162,000 - 388,000

Full time

14 days+

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Job summary

TikTok Inc. is seeking a seasoned ML Engineer to develop and deploy deep learning and LLM-powered systems for merchant tools and global e-commerce growth.

You will leverage large-scale e-commerce data to power agentic systems for CRM content, store decoration, automated email reply, and outreach optimization. The role requires strong ML fundamentals, Python proficiency, and 2+ years in ML engineering with NLP or growth-focused projects.

Qualifications

  • Master’s or PhD in Computer Science, AI, Statistics, OR related fields with data mining/deep learning experience.
  • Solid understanding of ML and DL fundamentals – classification, regression, NLP, model optimization.
  • Strong programming in Python; familiarity with ML frameworks (PyTorch, TensorFlow).
  • Ability to connect algorithms with business impact; highly self-driven with 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.

Responsibilities

  • Develop and deploy deep learning and LLM-powered systems for merchant tools and growth scenarios.
  • Leverage e-commerce data to power agentic systems for CRM content, outreach optimization, and store decoration.
  • Use ML models to predict seller performance, identify growth gaps, and provide agent-based recommendations.
  • Collaborate with product, data science, and operations to design and deliver 0-to-1 projects reshaping merchant growth across categories.
  • Build lead-scoring models, merchant tiering algorithms, and outreach optimization systems.
  • Apply data mining and predictive modeling to optimize pricing, promotions, and traffic allocation.
  • Communicate technical insights to both technical and non-technical stakeholders.

Skills

Python programming
ML/DL fundamentals
Data mining & modeling
Communication skills
Ownership & curiosity

Education

Master’s or PhD in CS/AI/Data science

Tools

PyTorch
TensorFlow

Job description

Team Introduction: 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.

Responsibilities
  1. Develop and deploy deep learning and LLM-powered systems for merchant operational tools and global e-commerce growth scenarios.
  2. 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.
  3. Use ML models to predict seller performance, identify growth gaps, and provide agent-based recommendations (e.g., campaign design, pricing, and promotions).
  4. 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.).
  5. Build lead-scoring models, merchant tiering algorithms, outreach optimization systems, and knowledge graphs to enhance onboarding and retention efficiency.
  6. Apply data mining and predictive modeling to optimize product pricing, promotion, and traffic allocation strategies.
  7. Communicate technical insights effectively to both technical and non-technical stakeholders, fostering a collaborative, data-driven culture.
Minimum Qualifications
  1. Master’s or PhD degree in Computer Science, Artificial Intelligence, Statistics, Operations Research, or related fields, with experience in data mining or deep learning.
  2. Solid understanding of ML and deep learning fundamentals - classification, regression, NLP, and model optimization.
  3. Strong programming skills in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
  4. Demonstrated ability to connect algorithms with business impact; highly self-driven with strong ownership and curiosity.
  5. 2+ years of experience as an ML Engineer, ideally in NLP, recommendation, marketing, or growth algorithms.
  6. Excellent analytical, teamwork, and communication skills.
Preferred Qualifications
  1. Experience in applied LLMs, multi-agent systems, or RAG (retrieval-augmented generation) pipelines.
  2. Published work in top-tier conferences (KDD, NeurIPS, ICML, SIGIR, WSDM, WWW, AAAI, IJCAI, RecSys, etc.) or success in ML competitions.
  3. Hands-on experience in e-commerce or other large-scale, data-intensive production environments.
  4. Passion for building agentic systems that drive real-world business outcomes.
Job Information

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:
  • Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
  • Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
  • Exercising sound judgment.
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