Machine Learning Engineer
Kasmoglobal
Pay not stated in the posting
Posted 11 months ago · Confirmed live 1 week ago
Skills this job asks for
- BigQuery
- Machine Learning Models
- MLOps
- Python
- Jira
- Machine Learning Concepts
- SharePoint
- Sprint Planning
- SQL
- Fraud Modeling
- MLlib
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At a glance
- Type
- Contract
- Level
- Not stated
- Experience
- Not stated
- Work model
- Not stated
- Schedule
- Not stated
- Education
- Not stated
- Benefits
- Not stated
- Team
- Engineering
Description
Title - Machine Learning Engineer
Location - San Jose, CA/Chicago, IL
Duration - 18 months contract with a possible extension
What You'll Do :
• Redesign and optimize PayPal's MLOps and decision platform for fraud detection
• Architect large-scale big-data infrastructure to enable use of cutting-edge machine learning models for real-time fraud prevention.
• Collaborate with data scientists and platform engineers to automate workflow
• Provide solutions that ensure compliance, security, and maintainability across the fraud detection ecosystem.
• Work with high-dimensional datasets and leverage tools like Python, PySpark, and Big Query to develop robust workflows for fraud signal detection.
• Standardize rules and decision processes while enabling dynamic rule updates and analytics within the fraud detection platform.
• Collaborate across multidisciplinary teams in engineering, product development, and data science to scale solutions globally.
• Tasks will be distributed via our Jira board/sprint planning/grooming cycle.
• Team will have a regular standup on each task (at least twice a week but open for daily if needed or any blockers)
• During the onboarding, it would require more interactions with Engg/Product/US Risk core teams but once onboarded, it would be 50/50.
• Team work mostly within Jira board from tasks assignments and tracking.
• Code would be in our centralized GitHub repo.
• Updates/documentation would be either in wiki page or our SharePoint/share drive.
You would get chance to design and implement scalable solutions to optimize fraud detection systems, spanning model development, feature engineering, and rule-based systems. You will collaborate closely with cross-functional teams, including data scientists, engineers, and product managers, to ensure our platform sets a new global standard for efficacy and innovation.
You will address critical business challenges, develop advanced automation frameworks, and integrate cutting-edge machine learning techniques to enhance decision-making capabilities. By joining us, you will not only contribute to PayPal's fraud detection efforts but leave a lasting impact on the financial security of millions of users around the globe.
Top Skills:
Location - San Jose, CA/Chicago, IL
Duration - 18 months contract with a possible extension
What You'll Do :
• Redesign and optimize PayPal's MLOps and decision platform for fraud detection
• Architect large-scale big-data infrastructure to enable use of cutting-edge machine learning models for real-time fraud prevention.
• Collaborate with data scientists and platform engineers to automate workflow
• Provide solutions that ensure compliance, security, and maintainability across the fraud detection ecosystem.
• Work with high-dimensional datasets and leverage tools like Python, PySpark, and Big Query to develop robust workflows for fraud signal detection.
• Standardize rules and decision processes while enabling dynamic rule updates and analytics within the fraud detection platform.
• Collaborate across multidisciplinary teams in engineering, product development, and data science to scale solutions globally.
• Tasks will be distributed via our Jira board/sprint planning/grooming cycle.
• Team will have a regular standup on each task (at least twice a week but open for daily if needed or any blockers)
• During the onboarding, it would require more interactions with Engg/Product/US Risk core teams but once onboarded, it would be 50/50.
• Team work mostly within Jira board from tasks assignments and tracking.
• Code would be in our centralized GitHub repo.
• Updates/documentation would be either in wiki page or our SharePoint/share drive.
You would get chance to design and implement scalable solutions to optimize fraud detection systems, spanning model development, feature engineering, and rule-based systems. You will collaborate closely with cross-functional teams, including data scientists, engineers, and product managers, to ensure our platform sets a new global standard for efficacy and innovation.
You will address critical business challenges, develop advanced automation frameworks, and integrate cutting-edge machine learning techniques to enhance decision-making capabilities. By joining us, you will not only contribute to PayPal's fraud detection efforts but leave a lasting impact on the financial security of millions of users around the globe.
Top Skills:
- Big Query, Python, SQL
- Understand the production systems architect and offline data overview
- Machine Learning experience
About Kasmoglobal
Kasmoglobal