ML Engineer: Knowledge Graphs for E-commerce

Ecommerce Guide; San Jose (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401(k) Savings Plan With Company Match

Paid Parental Leave

Short-term Disability Coverage

Long-term Disability Coverage

Life Insurance

Wellbeing Benefits

Paid Holidays

Paid Sick Days

Paid Personal Time

Job summary

Ecommerce Guide is seeking a researcher/developer to build large-scale knowledge graphs for e-commerce products, enhancing feed ranking, recommendations, and ads. You will work with product managers and data scientists to map buyer-product relationships and create scalable knowledge maps.

The role requires contributions across ML/NLP, with hands-on work in Python/C++/Go/Java and modern ML frameworks. Strong collaboration and problem-solving in a product-driven environment are essential.

Qualifications

• Bachelor's or Master's degree in CS or related field.
• Exposure to machine learning, NLP, and proficiency in Python, C++, Go, or Java.

Responsibilities

• Develop and construct knowledge graphs for e-commerce products to improve feed ranking, recommendations, and advertisements.
• Collaborate with product managers and data scientists to architect knowledge maps detailing buyer and product connections.

Skills

Machine Learning

Natural Language Processing

Multimodal Systems

Computer Vision

C++

Python

Go

Java

TensorFlow

PyTorch

Text Classification

Text Matching

Sequence Labeling

Knowledge Graphs

Text Mining

Deep Learning

Education

Bachelor's degree in Computer Science

Master's degree in Computer Science

Tools

TensorFlow

PyTorch

Job description

Ecommerce Guide is seeking a researcher/developer to build large-scale knowledge graphs for e-commerce products, enhancing feed ranking, recommendations, and ads. You will work with product managers and data scientists to map buyer-product relationships and create scalable knowledge maps.

The role requires contributions across ML/NLP, with hands-on work in Python/C++/Go/Java and modern ML frameworks. Strong collaboration and problem-solving in a product-driven environment are essential.