PayPal is looking for a Machine Learning Engineer to design, develop, and implement machine learning models and algorithms that solve complex business problems. You'll work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions, building scalable pipelines and deploying models into production.
What You'll Do
- 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.
What We're Looking For
- Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
- 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.
Technical Stack
- TensorFlow
- PyTorch
- scikit-learn
- AWS
- Azure
- GCP
Team & Environment
Work closely with data scientists, software engineers, and product teams.
Benefits & Compensation
- Comprehensive, choice-based programs supporting physical, emotional, and financial wellbeing.
- Generous paid time off.
- Healthcare coverage for you and your family.
- Resources to create financial security and support your mental health.
- Compensation: $159,500.00 - $236,500.00 Annually (San Jose, California)
Work Mode
This is a hybrid role based in San Jose, California.
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.
