Sr Machine Learning Engineer

PayPal; San Jose (CA); On-site; USD 159,500 - 236,500; Full time

Benefits offered by this job

Generous paid time off

Healthcare coverage

Financial security resources

Mental health support

Job summary

PayPal is seeking to hire a Machine Learning Engineer to design, develop, and implement machine learning models and algorithms. You will work closely with data scientists and product teams to enhance services with innovative AI/ML solutions, building scalable ML pipelines to improve customer experiences.

The ideal candidate has at least 5 years of experience and a Bachelor's degree. The position is based in San Jose, California, offering a competitive salary range of $159,500.00 - $236,500.00 annually plus performance bonuses and benefits.

Qualifications

• Minimum of 5 years of relevant work experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms for data processing and model deployment.

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.

Skills

Machine Learning

Data Analysis

TensorFlow

PyTorch

scikit-learn

AWS

Azure

GCP

Education

Bachelor's degree in a relevant field

Job description

Job Summary

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Essential 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.

Minimum Qualifications

• 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.

Additional Responsibilities & Preferred Qualifications

• Additional responsibilities and preferred qualifications details omitted for brevity.

Compensation

The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: San Jose, California ($159,500.00 - $236,500.00 Annually). Additional compensation may include an annual performance bonus, equity, or other incentive compensation, as applicable.

Benefits

At PayPal, we offer comprehensive, choice‑based programs to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.

Equal Employment Opportunity

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. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at [e-mail].