San Jose Technology - Algorithm Global Frontier Tech Recruitment Program - Intern

Ellis Technologies, Inc.; San Jose (CA); On-site; USD 68,191 - 97,120; Part time

Benefits offered by this job

Health insurance

Paid holidays

Paid sick time

Job summary

Ellis Technologies, Inc. is seeking a Research Scientist Intern to join their Global E-commerce team in San Jose. The position is focused on building advanced recommendation systems and includes hands-on learning alongside industry experts.

The candidate will work on projects involving machine learning, AI technologies, and big data frameworks. The internship offers day-one access to health benefits and a competitive hourly rate.

Qualifications

• Currently pursuing a PhD in a technical discipline.
• Strong foundation in machine learning and AI technologies.
• Familiarity with big data frameworks like Hadoop and Spark.

Responsibilities

• Build industry-leading recommendation systems.
• Explore generative recommendation techniques.
• Deliver end-to-end machine learning solutions.
• Optimize algorithms for recommendation performance.

Skills

Machine Learning

AI Technologies

Big Data Frameworks

TensorFlow

PyTorch

Computer Vision

Natural Language Processing

Education

PhD in Computer Science or related discipline

Tools

Hadoop

MapReduce

Spark

Job description

Research Scientist Intern – E-commerce Recommendation (LLM Applications)

Location: San Jose

Employment Type: Intern

Job Code: A38740

Overview

We are looking for talented PhD students to join our Global E-commerce team in 2027. This internship blends hands‑on learning, community events, and collaboration with industry experts to contribute to our products, research, and emerging technologies.

As part of our Global E-commerce system built on TikTok Shop, you will help build advanced recommendation engines, integrated multilingual, multimodal foundation models, and agent frameworks for demand forecasting, traffic allocation, and personalized recommendation.

Responsibilities

• Build industry‑leading recommendation systems that improve user experience, content ecosystem, and platform security.
• Explore generative recommendation techniques, including diffusion models, prompt learning, and multimodal content generation.
• Build multi‑modal and cross‑scenario systems enabling unified recommendation across livestreams, short videos, and search.
• Deliver end‑to‑end machine learning solutions to address critical product challenges.
• Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.
• Work with cross‑functional teams to design product strategies and build solutions to grow TikTok in important markets.

Qualifications

Minimum Qualifications

• Currently pursuing a PhD in Computer Science, Computer Engineering, or a related technical discipline.
• Strong foundation in machine learning, with knowledge of cutting‑edge AI technologies; publications or competition experience are preferred.
• Familiarity with big data frameworks such as Hadoop, MapReduce, and Spark.
• Experience with TensorFlow or PyTorch for model training and deployment; understanding of training acceleration techniques such as mixed precision and distributed training.

Preferred Qualifications

• Knowledge of model compression and inference acceleration techniques (quantization, pruning, distillation, TensorRT optimization).
• Expertise in at least one of the following areas:
• Computer Vision & Multimodality – research experience, large‑scale multimodal models, integration of LLMs with visual representations.
• Natural Language Processing – research experience with LLMs, pretraining, cross‑lingual learning, NLP model deployment.

Job Information

Hourly rate: $60–$60.

Benefits

Interns have day‑one access to health, life insurance, and wellbeing benefits. They receive 10 paid holidays, paid sick time (56 hrs if hired first half of the year, 40 hrs if hired second half), and may be eligible for a housing allowance if not working 100 % remote.

Equal Employment Opportunity

Qualified applicants with arrest or conviction records will be considered in accordance with all federal, state, and local laws. The Company reserves the right to modify or change these benefit programs at any time.