Machine Learning Engineer
About The Position
PayPal, Inc. seeks Machine Learning Engineer in Austin, TX. The role involves gathering, analyzing, and implementing high-impact statistical models and AI applications across various business functional areas, with a focus on Natural Language Processing (NLP) models and Generative AI. Responsibilities include conducting quantitative and qualitative model validation according to internal policies and industry standards, maintaining technical documentation for AI/ML model development and validation, and collaborating with business units and model developers to ensure timely remediation of model issues. The engineer will build relationships with stakeholders from diverse teams such as data science, engineering, product, customer service, compliance, and audit. Additionally, the role requires researching the latest AI/ML advancements and exploring innovation opportunities. Partial telecommuting is permitted from within a commutable distance.
Requirements
- Master’s degree, or foreign equivalent, in Computer Science, Engineering, Data Science, or a closely related field plus one year of experience in the job offered or a related occupation.
- Experience developing and deploying statistical model and data-driven applications using Python to analyze multi-terabyte datasets, generate actionable insights and support decision-making for business operation (1 year).
- Experience analyzing and interpreting credit reports and credit data to derive business insights (1 year).
- Experience querying, manipulating, and analyzing multi-terabyte datasets, including external bureau data, using SQL to enable advanced business analytics in large-scale operational environments (1 year).
- Experience building interactive dashboard and data visualizations with Tableau/Looker Studio to communicate customer analytics to stakeholders (1 year).
- Experience designing, implementing, and deploying machine learning models for business applications (1 year).
- Experience extracting, transforming, and selecting meaningful features from credit datasets to improve model performance (1 year).
- Experience conducting statistical analysis and hypothesis testing to uncover meaningful trends and generate actionable recommendations (1 year).
- Experience working with Generative AI architectures, including Large Language Model (LLMs), to analyze, automate, and enhance internal tool process – such as developing NLP-driven transcription and summarization tools (1 year).
Responsibilities
- Gather, analyze and implement high-impact statistical models and AI applications in various business functional areas, focusing on but not limited to Natural Language Processing (NLP) models and Generative AI.
- Conduct quantitative and qualitative model validation in line with internal Model Risk Management Policy and industry standard to identify and report issues arising from model data, model design and model use.
- Maintain technical documentation of AI/ML model development and validation.
- Collaborate with business units and model developers to ensure model issues are agreed and remediated in a timely manner.
- Build effective relationship with stakeholders from various teams such as data science, engineering, product, customer service/complaints, compliance, audit.
- Research latest AI/ML advancements and explore opportunities for innovation.
Benefits
- Generous paid time off
- Healthcare coverage for you and your family
- Resources to create financial security
- Support your mental health
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
