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Machine Learning Engineer

$70k - $170k
Full-time

SuprAIJobs

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Machine Learning Engineer

PayPal

  • USD 70K-170K
  • Full Time
  • San Jose, CA
  • On-site

At PayPal (NASDAQ: PYPL), we believe that every person has the right to participate fully in the global economy. Our mission is to revolutionize commerce globally to make moving money, selling and shopping, personalized and secure.

Job Description Summary

PayPal is seeking a talented Machine Learning Scientist join our Global Machine Learning team, driving the development of AI-driven solutions that will shape the future of PayPal. You design and develop ML solutions including personalization, recommendation, and ranking of deals and promotion across our Brands and surfaces. Your goal will be to optimize the customer journey through personalized, thrilling experiences.

With a strong background in Machine Learning and practical experience in building and implementing large scale predictive models to solve business problems, you will help to bring insights and identify additional opportunities from Data & Machine Learning to market.

Meet our team

PayPal is a global leader in online payments and democratization of financial services, providing payment solutions for hundreds of millions of customers all over the world. In a high-impact and high-visibility environment, you will have the opportunity of utilizing PayPal’s large-scale infrastructure (including network graph assets) to design and develop large-scale ranking and recommendation systems powering content on novel user interface designs to fundamentally enhance customer experience and engagement.

Your way to impact

As an ML engineer, you will have the opportunity to work on large-scale ranking and recommendation systems for sequential content consumption on newly installed user interface designs at PayPal. The solutions developed by you will aid in building novel and meaningful graph-based community assets around the PayPal network of consumers and merchants, to ultimately drive key product and marketing KPIs associated with customer experience, engagement and the revenue bottom line.

Your day to day

As a Machine Learning Scientist you will be responsible for:

  • Creating innovative AI/ML solutions that enhance personalization for PayPal users, with a focus on ranking and recommendation algorithms.
  • Writing scalable, production-quality code to deploy models on company infrastructure, optimizing for performance and efficiency.
  • Collaborating with cross-functional teams, including engineering, product, and marketing, to design, develop, and track key performance indicators (KPIs) for ranking and recommendation models.
  • Conducting experiments to measure these KPIs, as well as deriving actionable insights from the data, to continually improve the technology and drive business outcomes.

What Are We Looking For

  • Advanced degree (MS or PhD) in quantitative science or engineering field (for example: Computer Science, Statistics, Mathematics, Operation Research) with a minimum of 2 years of hands-on experience for MS as an individual contributor.
  • Proven expertise in designing and developing AI/ML models for ranking and recommendation systems, with in-depth understanding of both traditional collaborative/content-based recommendation methods and cutting-edge deep learning algorithms, reinforcement learning, and bandit techniques.
  • Demonstrated ability to write scalable high quality code in Python, Java, Scala or a similar programming language, and to design and implement data engineering pipelines using technologies like Hive, SQL, BigQuery, or Spark.
  • Proficiency in machine learning frameworks and packages, such as Tensorflow and PyTorch.

Nice to Haves

  • Experience with Graph-based algorithms and infrastructure.
  • Prior experience working in a cloud-based environment such as GCP.
  • Hands-on experience with conducting experiments in various areas of personalization and causal inferencing.

Subsidiary

Additional Job Description

PayPal

Travel Percent

PayPal is committed to fair and equitable compensation practices.

Actual Compensation is based on various factors including but not limited to work location, and relevant skills and experience.

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit

The U.S. national annual pay range for this role is

to

Our Benefits

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit

Who We Are

Click Here to learn more about our culture and community.

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. For more information, visit , and

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at View email address on us.fitly.work.

Any general requests for consideration of your skills, please Join Our Talent Community.

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Back

Machine Learning Engineer

PayPal

  • USD 70K-170K
  • Full Time
  • San Jose, CA
  • On-site

Meet our team

PayPal is a global leader in online payments and democratization of financial services, providing payment solutions for hundreds of millions of customers all over the world. In a high-impact and high-visibility environment, you will have the opportunity of utilizing PayPal’s large-scale infrastructure (including network graph assets) to design and develop large-scale ranking and recommendation systems powering content on novel user interface designs to fundamentally enhance customer experience and engagement.

Your way to impact

As an ML engineer, you will have the opportunity to work on large-scale ranking and recommendation systems for sequential content consumption on newly installed user interface designs at PayPal. The solutions developed by you will aid in building novel and meaningful graph-based community assets around the PayPal network of consumers and merchants, to ultimately drive key product and marketing KPIs associated with customer experience, engagement and the revenue bottom line.

Your day to day

As a Machine Learning Scientist you will be responsible for:

  • Creating innovative AI/ML solutions that enhance personalization for PayPal users, with a focus on ranking and recommendation algorithms.
  • Writing scalable, production-quality code to deploy models on company infrastructure, optimizing for performance and efficiency.
  • Collaborating with cross-functional teams, including engineering, product, and marketing, to design, develop, and track key performance indicators (KPIs) for ranking and recommendation models.
  • Conducting experiments to measure these KPIs, as well as deriving actionable insights from the data, to continually improve the technology and drive business outcomes.

What Are We Looking For

  • Advanced degree (MS or PhD) in quantitative science or engineering field (for example: Computer Science, Statistics, Mathematics, Operation Research) with a minimum of 2 years of hands-on experience for MS as an individual contributor.
  • Proven expertise in designing and developing AI/ML models for ranking and recommendation systems, with in-depth understanding of both traditional collaborative/content-based recommendation methods and cutting-edge deep learning algorithms, reinforcement learning, and bandit techniques.
  • Demonstrated ability to write scalable high quality code in Python, Java, Scala or a similar programming language, and to design and implement data engineering pipelines using technologies like Hive, SQL, BigQuery, or Spark.
  • Proficiency in machine learning frameworks and packages, such as Tensorflow and PyTorch.

Nice to Haves

  • Experience with Graph-based algorithms and infrastructure.
  • Prior experience working in a cloud-based environment such as GCP.
  • Hands-on experience with conducting experiments in various areas of personalization and causal inferencing.

Who We Are

Click Here to learn more about our culture and community.

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. For more information, visit , and

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at View email address on us.fitly.work.

Any general requests for consideration of your skills, please Join Our Talent Community.

Explore more AI career opportunities

Machine Learning Jobs

Data Science Jobs

Natural Language Processing Jobs

Computer Vision Jobs

Artificial Intelligence Jobs

Data Engineering Jobs

MLOps Jobs

Robotics Jobs

AI Research Jobs

AI Ethics Jobs

AI Hardware Jobs

Automation Jobs

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