招聘
福利待遇
•401(k)
•Equity
•Parental Leave
•Unlimited Pto
必备技能
Java
Kotlin
Python
Machine Learning
Data Structures
Algorithms
Statistics
TensorFlow
PyTorch
Keras
scikit-learn
At e Bay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
About the Role & Team:
Global Payments and Risk is at the forefront of innovation, integrating ground breaking technologies into our products and services. We are dedicated to using the power of machine learning to solve real-world problems, improve user experiences, and drive business outcomes. Join us in shaping the future with your expertise and passion for technology.
- We are seeking a motivated Software Engineer with a strong background in software development and hands-on experience in machine learning. The ideal candidate should have a platform-centric approach and a proven track record in applying machine learning techniques to develop scalable software solutions. You will be instrumental in crafting innovative applications that safeguard our marketplace to mitigate risks, and curtail financial losses. Join our collaborative team that thrives on creativity and resourcefulness to tackle sophisticated challenges.What you will accomplish:
- Design, deliver, and optimize high-performance, large-scale applications, data pipelines, and ML service infrastructure with exceptional speed and reliability.
- Enhance core products by skillfully integrating, fine-tuning, and deploying advanced machine learning models for optimal performance and impact.
- Command the full software development lifecycle—from initial design and architecture to coding, testing, deployment, and maintenance—while producing clean, efficient, and documented code.
- Develop and execute sound technical strategies for complex projects, taking into account business goals, timelines, and long-term impact.
- Work closely with product managers and partners to translate business requirements into robust technical solutions, ensuring alignment across teams.
- Take ownership of cross-team engineering efforts and guide junior team members, setting a high standard for technical excellence and professional growth.
- Drive innovation by developing novel solutions to challenging problems and actively contribute to a culture of knowledge sharing by both teaching and learning from others.
What you will bring:
-
Masters or Bachelors degree in Computer Science or a related field with 10 years of experience in building large-scale distributed applications and backend services.
-
Expert with Java, Kotlin to build server side technologies is required.
-
A solid foundation in Data Structures, Algorithms, Object-Oriented Programming, Software Design/architecture, and core Statistics knowledge
-
Experience in the close examination of data, computation of statistics, and deriving of data insights
-
Proven experience designing and operating Big Data processing pipelines (Hadoop, Spark) and working with NoSQL databases or key-value stores (e.g., MongoDB, Redis).
-
Hands-on experience with the end-to-end lifecycle of machine learning, including model deployment and application at scale. Experience in AI research or industrial recommendation systems is a significant plus.
-
Experience with cloud services and familiarity with Large Language Models (LLMs) or prompt engineering is highly desirable.
-
A passion for technical excellence, excellent communication skills, and a “can-do” attitude with a willingness to learn and master new technologies.
-
Proven expertise in Python and ML libraries such as scikit-learn, Tensor Flow, Py Torch, Keras.
-
Strong understanding of machine learning fundamentals, algorithms, and model evaluation techniques.
-
Hands-on experience with ML Ops tools and best practices.
-
Proficiency in working with large scale data in hadoop and spark.
-
Proficient with prediction accuracy, latency, throughput, confidence scores, and drift (data & concept).
Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talentebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.
The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our Privacy Center for more information.
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关于eBay

eBay
PubliceBay Inc. is an American multinational e-commerce company based in San Jose, California, that allows users to buy or view items via retail sales through online marketplaces and websites in 190 markets worldwide.
10,001+
员工数
San Jose
总部位置
$28.1B
企业估值
评价
3.8
5条评价
工作生活平衡
4.2
薪酬
2.5
企业文化
4.0
职业发展
2.8
管理层
3.5
优点
Good work-life balance
Great culture and environment
Nice colleagues and supportive people
缺点
Limited opportunities for growth
Old technology and systems
Call quotas and difficult customers
薪资范围
2,731个数据点
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Data Science Analyst 2
1份报告
$174,200
年薪总额
基本工资
$134,000
股票
-
奖金
-
$174,200
$174,200
面试经验
4次面试
难度
3.0
/ 5
时长
14-28周
体验
正面 0%
中性 75%
负面 25%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Past Experience
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