eBay

HQ
San Jose
Total Offices: 2
26,035 Total Employees

eBay Benefits Overview

Compensation + Benefits

Offers 401(K)

Offers life insurance

Offers supplemental life insurance

Offers accidental death & dismemberment insurance

Offers disability insurance

Offers charitable contribution matching

Offers occupational accident insurance

Provides adoption assistance

Provides family medical leave

Provides fertility benefits

Offers childcare benefits

Offers generous parental leave

Offers company equity

Offers performance bonuses

Offers employee stock purchase plan

Offers employee discounts

Offers dental insurance

Offers health insurance

Offers mental health benefits

Offers dependent care

Offers Flexible Spending Account (FSA)

Offers vision insurance

Offers Health Savings Account (HSA)

Company Culture

Provides commuter benefits

Offers legal assistance

Provides a mobile phone discount

Utilizes a flexible work schedule

Offers a remote work program

Offers diversity-based Employee Resource Groups

Work-Life Balance + Wellbeing

Offers company-sponsored outings

Offers gym membership

Offers an Employee Assistance Program (EAP)

Offers generous PTO

Provides paid holidays

Provides bereavement leave

Offers unpaid extended leave

Offers paid volunteer time

Offers sabbatical leave

Provides military leave

Career Growth + Development

Provides customized development tracks

Job training & conferences

Provides tuition assistance

Recently posted jobs

4 Hours AgoSaved
In-Office
Austin, TX, USA
eCommerce • Retail
Manage AI and automation initiatives at eBay's Finance Innovation & Transformation team by overseeing project execution, collaborating across teams, and ensuring adoption of solutions.
YesterdaySaved
In-Office
Austin, TX, USA
eCommerce • Retail
As a Full Stack Engineer at eBay, you will design and build IAM applications, integrate AI/ML capabilities, and improve identity governance while collaborating across teams.
2 Days AgoSaved
In-Office
Austin, TX, USA
eCommerce • Retail
Develop and fine-tune machine learning models (NLP and multimodal) to improve listing quality and detect mismatches, restricted items, and fraud. Build large-scale data pipelines for ingestion, cleaning, annotation, and feature engineering. Conduct research on anomaly detection, run experiments and A/B tests, evaluate models against business metrics, and collaborate with engineers, product managers, and compliance experts.