Machine Learning Engineer Intern (Monetization Technology - Ads Core Global) - 2027 Summer

NWU; San Jose (CA); On-site; USD 34,000 - 55,000; Full time

Job summary

NWU in San Jose invites a student intern to help optimize the advertising funnel using ML/DL tools. You will research and develop a global delivery system, design scalable frameworks, and collaborate with product teams across scenarios with worldwide impact.

Ideal candidates are pursuing a BS in CS/Math/Stats, with solid C/C++ and Python skills, Linux experience, and knowledge of statistics and deep learning. Familiarity with TF/PyTorch is a plus.

Qualifications

• Pursuing a Bachelor's degree in CS, Math, Statistics or related field.
• Solid programming skills in C/C++ and Python; Linux experience.
• Good analytical thinking with knowledge in statistics.
• Strong grounding in deep learning concepts and techniques.
• Familiar with one or more ML frameworks (TF, PyTorch, MXNet).
• Knowledge of Factorization Machines, Uplift Modeling or Reinforcement Learning is a plus.
• Basic understanding of large-scale recommender and ads serving concepts.

Responsibilities

• Assist in optimizing efficiency across the advertising funnel.
• Research and develop global advanced advertising delivery systems with ML/DL.
• Design system frameworks and standards to improve efficiency for different verticals.
• Collaborate with product and business teams globally.

Skills

C/C++

Python

Linux development

DS & algorithms

Statistics

Deep learning concepts

ML frameworks knowledge

TensorFlow

PyTorch

Reinforcement Learning

Factorization Machine

Uplift Modeling

Diffusion Models

Education

Bachelor's degree in Computer Science, Mathematics, Statistics

Tools

TensorFlow

PyTorch

MXNet

Job description

Your Role

Here’s what you will be doing:

• Assist in optimizing efficiency across the entire advertising funnel, including Recall & Rough-sort, Fine-sort (CTR/CVR), format/creative personalization, and system resource allocation.
• Research and develop a global advanced advertising delivery system using frontier technologies such as ML/DL, RL, LLM, and scaling laws in ads recommendation.
• Design and set up system frameworks and standards to continuously improve overall efficiency and meet different vertical business needs.
• Collaborate with product and business teams from various scenarios with global impact.

About You

The company is looking for candidates who meet the following qualifications:

• Currently pursuing a Bachelor's degree in Computer Science, Mathematics, Statistics, or a related technical discipline.
• Solid programming skills, proficient in C/C++ and Python; familiar with basic data structures and algorithms; experienced with Linux development environment.
• Good analytical thinking capability with essential knowledge and skills in statistics.
• Strong theoretical grounding in deep learning concepts and techniques.
• Familiarity with architecture and implementation of at least one mainstream machine learning framework (TensorFlow, PyTorch, MXNet), including its architecture and implementation mechanisms.
• Preferred knowledge in one or more of the following: Factorization Machine, Uplift Modeling, Diffusion Models, Reinforcement Learning.
• Basic understanding of large recommendation system and ads serving system concepts.