Job Summary:This job will drive the strategic vision and development of cutting-edge 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.
Job Description:Essential Responsibilities: - Define and drive the strategic vision for machine learning initiatives across multiple teams or projects.
- Lead the development and optimization of state-of-the-art machine learning models.
- Oversee the preprocessing and analysis of large datasets.
- Deploy and maintain ML solutions in production environments.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models, making necessary adjustments.
- Mentor and guide junior engineers and data scientists.
- Publish research findings and contribute to industry discussions.
- Lead the development of new methodologies and frameworks for ML applications.
Minimum Qualifications:- 10+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.
- Deep expertise with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Extensive experience with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
- Proven track record of leading the design, implementation, and deployment of machine learning models.
Additional Responsibilities & Preferred Qualifications:- 10+ years in ML engineering, with deep expertise in recommendation systems, search ranking, or personalization at consumer scale
- Production experience with learning-to-rank, contextual bandits, or real-time recommendation systems serving millions of users
- Track record building ML that drives business metrics - you think in terms of engagement, conversion, and retention, not just model accuracy
- Experience with social platform ML: feed ranking, social graph models, content discovery, or network growth - at a company where social interaction is core to the product
- Strong platform design skills - feature stores, model serving, experiment infrastructure
- Experience with graph-based ML: social graph embeddings, transaction graphs, or knowledge graphs
- Strong data engineering instincts - BigQuery, Spark, Airflow, dbt - you understand the full pipeline from raw data to model prediction
Subsidiary:PayPal
Travel Percent:0
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:
Primary Location | Pay Range:San Jose, California | ($242,000.00 - $359,150.00 Annually)
Additional Location(s) | Pay Range:No other locations are assigned to this requisition currently.
Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.
For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.
Our Benefits:At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why 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.
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We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.
