PayPal

1 month ago

Sr Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Senior-level Machine Learning Data Scientist & Engineer within PayPal’s Global Fraud Prevention, focused on automation, tools, and infrastructure to enhance risk decisioning at scale. Lead end-to-end data science initiatives—from data mining and feature engineering to model development and operationalization—collaborating with product, engineering, and analytics teams to deliver impactful fraud-detection solutions.

Location: Dublin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Develop and optimize machine learning models for various applications.
•Preprocess and analyze large datasets to extract meaningful insights.
•Deploy ML solutions into production environments using appropriate tools and frameworks.
•Collaborate with cross-functional teams to integrate ML models into products and services.
•Monitor and evaluate the performance of deployed models.

Pay and Benefits

Perks:Health InsuranceRetirement

Key Requirements

•3+ years of relevant experience with a Bachelor’s degree or equivalent
•Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn
•Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment
•Several years of experience in designing, implementing, and deploying machine learning models
•Strong data preprocessing and feature engineering abilities

Experience:3+ yearsPaymentsFraudMachine learningData science

Education:Bachelor's

Skills:CommunicationCollaborationProblem-solvingTeamworkMentorship

Languages:English

Tech Stack:TensorFlowPyTorchScikit-learnAWSAzureGCPSQLPythonR

Company Brief

PayPal

Global online payments platform enabling digital and mobile payments, money transfers, and merchant services for consumers and businesses, supporting e‑commerce transactions across multiple currencies and payment methods.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1998

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

PayPal

1 month ago

Sr Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: Dublin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Develop and optimize machine learning models for various applications.
•Preprocess and analyze large datasets to extract meaningful insights.
•Deploy ML solutions into production environments using appropriate tools and frameworks.
•Collaborate with cross-functional teams to integrate ML models into products and services.
•Monitor and evaluate the performance of deployed models.

Pay and Benefits

Perks:Health InsuranceRetirement

Key Requirements

•3+ years of relevant experience with a Bachelor’s degree or equivalent
•Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn
•Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment
•Several years of experience in designing, implementing, and deploying machine learning models
•Strong data preprocessing and feature engineering abilities

Experience:3+ yearsPaymentsFraudMachine learningData science

Education:Bachelor's

Skills:CommunicationCollaborationProblem-solvingTeamworkMentorship

Languages:English

Tech Stack:TensorFlowPyTorchScikit-learnAWSAzureGCPSQLPythonR

Company Brief

PayPal

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1998

Website LinkedIn