Machine Learning Engineer Intern (E-Commerce Recommendation/Search Alliance) - 2027 Summer

TikTok

Seattle (WA)

On-site

USD 58,000 - 62,000

Full time

30 hours ago
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Benefits offered by this job

Health insurance
Day one health benefits
Housing allowance

Job summary

TikTok is seeking a campus intern to join the E‑commerce Alliance team, focused on building AI-powered affiliate tools and personalized recommendations for merchants and creators. You will work on cutting‑edge machine learning, ranking algorithms, and end‑to‑end experimentation in a fast‑moving, global platform.

You will collaborate with cross‑functional teams, gain hands‑on experience with production‑grade ML systems, and participate in development workshops during the internship.

Qualifications

  • Currently pursuing an undergraduate degree in software development, computer science, or computer engineering.
  • Strong grasp of data structures, algorithms, and problem solving.
  • Proficiency in machine learning, statistics, and big data concepts.

Responsibilities

  • Design and build ML, recommendation, and ranking algorithms for large‑scale e‑commerce.
  • Develop AI‑powered merchant operation systems and AI agents to optimize affiliate strategies.
  • Apply LLMs, NLP, and multimodal ML to drive growth for merchants and creators.
  • Collaborate with product managers and engineers to deploy research into production.
  • Prototype and productionize new AI technologies to shape intelligent commerce.
  • Build ML‑agents to accelerate experimentation and deployment workflows.

Skills

Data structures
Algorithms
Problem solving
ML knowledge
Statistics

Education

Undergraduate in CS/SE

Job description

Team Introduction: The E-commerce Alliance team connects merchants and creators across the TikTok Shop ecosystem. We help merchants achieve their business goals by building intelligent and automated affiliate operation tools, while providing creators with efficient and highly personalized product recommendations that make it easier to discover the right products and create high-quality content. By improving merchant–creator matching, recommendation, search, and end-to-end collaboration efficiency, we aim to expand merchants’ marketing opportunities, increase creators’ monetization potential, and deliver a more engaging and personalized shopping experience to TikTok users. Our team works on large-scale recommendation and search systems, intelligent affiliate operations, creator and product understanding, and machine learning solutions that impact commerce growth. We are looking for talented individuals to join us for an internship. Our internship program offers students hands‑on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.

Responsibilities
  • Design and build cutting‑edge machine learning, recommendation, and ranking algorithms to power large‑scale e‑commerce recommendation systems that deliver high‑quality, real‑time product recommendations for millions of users.
  • Develop AI‑powered merchant operation systems and AI agents that help merchants optimize affiliate strategies, improve business ROI, and lower the barrier to growing their business through automation.
  • Apply state‑of‑the‑art LLMs , NLP, and multimodal machine learning to discover new business opportunities , driving sustainable growth for both merchants and creators.
  • Collaborate closely with product managers, engineers, and cross‑functional teams to bring innovative AI solutions from research to production.
  • Stay at the forefront of advances in AI and machine learning, rapidly prototyping and productionizing new technologies to shape the future of intelligent commerce.
  • Build ML‑agents to automate algorithm development workflows, accelerating experimentation, model iteration, evaluation, and deployment.
Qualifications

Minimum Qualifications:

  • Currently pursuing a Undergraduate in Software Development, Computer Science, Computer Engineering or a related discipline
  • Strong grasp of data structures, algorithms, and top‑notch problem‑solving skills;
  • Profound knowledge in machine learning, statistics, and big data engineering.
Preferred Qualifications
  • Thorough understanding of data structures and algorithms, with excellent problem‑solving ability;
  • Deep Understanding of machine learning, statistics, scaling distributed computing, and big data engineering.
Job Information

【For Pay Transparency】Compensation Description (Hourly) - Campus Intern

The hourly rate range for this position in the selected city is $42.75- $42.75.

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.

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.
About TikTok

TikTok is the leading destination for short‑form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day. We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

TikTok Accommodation

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request

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