Research Scientist at PayPal

San Jose, California, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Jan, 26

Salary

0.0

Posted On

15 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Analysis, Model Deployment, Collaboration, NLP, Deep Learning, Statistical Machine Learning, Transformer Architectures, Attention Mechanisms, Distributed Training, Cloud Platforms, TensorFlow, PyTorch, JAX, DeepSpeed, Research Publications

Industry

Software Development

Description

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. 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 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. 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.)

Responsibilities

Develop and optimize machine learning models for various applications and deploy them into production environments. Collaborate with cross-functional teams to integrate ML models into products and services while monitoring their performance.