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Machine Learning Engineer

PayPal

Machine Learning Engineer

PayPal

San Jose, California, United States of America

·

On-site

·

Full-time

·

3w ago

This job will assist in designing, developing, and implementing machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Essential Responsibilities:

  • Assist in the development and optimization of machine learning models.
  • Preprocess and analyze datasets to ensure data quality.
  • Collaborate with senior engineers and data scientists on model deployment.
  • Conduct experiments and run machine learning tests.
  • Stay updated with the latest advancements in machine learning.

Minimum Qualifications:

  • Minimum of 2 years of relevant work experience and a Bachelor's degree or equivalent experience.
  • Familiarity with ML frameworks like TensorFlow or scikit-learn.
  • Strong analytical and problem-solving skills.

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About PayPal

PayPal

PayPal

Public

PayPal Holdings, Inc. is an American multinational financial technology company operating an online payments system in the majority of countries that support online money transfers; it serves as an electronic alternative to traditional paper methods such as checks and money orders.

25,000+

Employees

San Jose

Headquarters

$70B

Valuation

Reviews

3.2

24 reviews

Work Life Balance

3.5

Compensation

2.8

Culture

2.5

Career

2.7

Management

2.2

25%

Recommend to a Friend

Pros

Good benefits and company takes care of people

Helpful colleagues and good team environment

Work life balance and flexible culture

Cons

Frequent layoffs and restructuring

Poor management and lack of direction

Low pay increases and compensation issues

Salary Ranges

3 data points

Intern

Intern · MLE Intern

1 reports

-

total / year

Base

$59

Stock

-

Bonus

-

Interview Experience

7 interviews

Difficulty

3.6

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 57%

Negative 43%

Interview Process

1

Application Review

2

Online Assessment

3

Recruiter Screen

4

Technical Interview Rounds

5

System Design Interview

6

Hiring Manager Interview

7

Team Matching

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience