Machine Learning Engineer Intern; E-Commerce Graph- Summer
Listed on 2026-10-18
-
Software Development
Machine Learning/ ML Engineer, Data Scientist
Seattle
Employment TypeIntern
Job CodeA71682
ResponsibilitiesTeam Introduction:
The Knowledge Graph team is responsible for the neural network of e-commerce, which includes tasks such as categorizing products, influencers, and merchants, mining product information, and providing this data to the recommendation team. Additionally, they manage operations related to product tags and category attributes. When we come across a product, they determine whether it belongs to the clothing or sports category, who thie product will be suitable for, etc.
Furthermore, the team conducts competitive research, identifying top-performing items on the platform and analyzing why one similar product outperforms others. They are also involved in brand recognition. This team plays a pivotal role, in bridging various aspects of our business and maintaining close collaboration with other teams.
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.
Candidates may apply to a maximum of two positions across Our Company and its affiliates globally.
- Craft intricate knowledge graphs, encompassing areas like product/content insights and category/brand/SPU development;
- Architect knowledge maps detailing buyer and product connections.
- Currently pursuing a Undergraduate in Software Development, Computer Science, Computer Engineering or a related discipline.
- Experience in at least one of the technological areas:
- LLM, natural language generation, named entity recognition, machine translation, question answering, knowledge graph, information extraction, text mining and classification etc. - Computer vision, facial recognition, multimodal learning, object detection & tracking, image classification etc.
- Machine learning, transfer learning, graph embedding, representative learning, large-scale optimization, recommendation, reinforcement learning, etc.
- Strong coding skills in at least one of the following programming frameworks, e.g. Python, Java, C/C++, Spark etc.;
Familiar with at least one of the following deep learning frameworks, e.g., PyTorch, Tensor Flow, Keras etc. - Strong analytical and problem-solving skills;
- Preferred Qualifications:
- Familiarity with deep learning frameworks like Tensor Flow/PyTorch. - Coursework or projects related to text classification, text matching, sequence labeling, and knowledge graphs.
- Knowledge of domain adaptation, text mining, and unsupervised/semi-supervised methodologies.
- Experience with machine learning and deep learning algorithms, and text representation methods.
- Exposure to large-scale text data processing or tools like Hadoop/Spark/Hive/Flink.
- Work experience in e-commerce or the Internet industry is preferred
The hourly rate range for this position in the selected city is $42.75- $42.75.
BenefitsBenefits 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)…(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).