PayPal Research Scientist 

United States, California, San Jose 

259066233

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.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and 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.

Key Responsibilities:

• Research and develop large-scale foundation models, including continuous pre-training, supervised fine-tuning, and alignment techniques

• Design novel architectures and training methodologies for domain-specific language models in financial services

• Build scalable ML pipelines for foundation model training, evaluation, and deployment at enterprise scale

• Conduct rigorous experimentation and benchmarking to ensure model quality, safety, and performance

• Deploy foundation models into production environments to drive business insights and enhance customer experiences

• Collaborate with cross-functional teams to identify high-impact use cases and translate research into practical solutions

• Stay current with latest developments in LLM and LLM-Agent research and contribute to the broader AI/ML community through publications and open-source contributions

• Mentor junior researchers and contribute to technical strategy for foundation model initiatives

Preferred Qualifications:

• PhD in Computer Science, Machine Learning, AI, or related field with focus on large language models and LLM Agent

• 1-3+ years of hands-on experience training and deploying large-scale language models (7B+ parameters)

• Deep expertise in transformer architectures, attention mechanisms, and modern training techniques

• Experience with distributed training frameworks (PyTorch, JAX, DeepSpeed, etc.)

• Strong background in NLP, deep learning, and statistical machine learning

• Proven track record of research publications in top-tier venues (NeurIPS, ICML, ACL, etc.)

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

The US national annual pay range for this role is $137,500 to $236,500

Our Benefits:

Any general requests for consideration of your skills, please