Global Analytics & Data Sciences (GADS) serves as PayPal's enterprise Analytics & Data Science Solution(s)/Service(s) provider, consisting of different vertical and horizontal sub-portfolios such as consumer, merchant, risk, credit, customer operation, etc. Compliance & Privacy is a portfolio under GADS supporting Compliance & Privacy domains to enable us to fulfill regulatory requirements around Anti-Money Laundering (AML), Brand Risk Management (BRM), Sanctions Screening, Know Your Customer (KYC), and Data Privacy. We are developing AI/ML solutions to better aid detection, assisted investigation experience, and automated decisions.
Your way to impact-
We seek a dynamic and enthusiastic Machine Learning Engineer/Scientist to join our team. This role focuses on developing cutting-edge machine learning and deep learning solutions tailored to the compliance and privacy domains. If you are driven by innovation and possess a strong passion for machine learning technologies, we are excited to welcome you aboard!
Your day to day –
- Design, develop, and optimize advanced machine learning and deep learning models to solve real-world problems.
- Collaborate with cross-functional teams across various time zones to understand business requirements and transform them into robust technical solutions.
- Mentor junior team members and provide technical guidance.
- Lead code reviews and ensure best practices in software development and machine learning.
- Continuously evaluate emerging technologies or methodologies to improve the team's capabilities and maintain industry leadership.
What do you need to bring-
- Fresh graduates for PhD; 3+ year experience Machine Learning Engineer/Scientist or similar role for MS.
- Masters, PhD, or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.)
- Experience with end-to-end machine learning project lifecycle, from conception to production.
- Passionate to learn the state-of-the-art machine learning framework and algorithms in academia and industry.
- Proven experience in employing mathematical, statistical, and machine learning methods on real-world problems
- Proficient in data mining and familiar with SQL, BigQuery, Python, etc.
- Proficient in deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
- Knowledge of specialized areas such as NLP or computer vision.
- Exceptional written and verbal communication skills in English, capable of influencing cross-functional teams.
- Industry experience in compliance and privacy domains is a plus.
- Experience working in a multinational company is a plus.
- Familiarity with Large Language Models (LLMs) is a plus.
- Publications in prominent journals or conferences in the field of AI or successful AI/ML-related patent applications are pluses.
