PayPal is hiring for the role of AI/ML Engineer!

Responsibilities of the Candidate:

• Develop, optimize, fine-tune Generative AI/LLM models/AI Solutions that can be integrated with numerous applications, support thousands of tenants, and operate at scale in production to support various Paypal AI Personalization initiatives  
• Deploy, monitor, and maintain Machine Learning models and build AI Products in production environments, ensuring optimal performance and reliability. 
• Perform performance evaluations of the LLM models, Implement LLMOps processes to run the end-to-end lifecycle of LLM's 
• Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. 
• Demonstrate effective communication skills by clearly articulating complex technical concepts to both technical and non-technical stakeholders. 
• Facilitate seamless collaboration with cross-functional teams from Business and Technology domains to align project goals, gather requirements, provide technical support and drive successful project outcomes. 

Requirements:

• Masters/bachelor’s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technical expertise in one or more of the above-mentioned areas or equivalent practical experience.   
• The ideal candidate will have a deep understanding of distributed systems, cloud infrastructure, and ML operations 
• Solid Understanding of machine learning concepts, algorithms, and techniques, developing and deploying machine learning models.    
• Expert in multiple Programming/scripting languages, i.e., Python, Java, Scala, SQL, NoSQL (like HBase, Redis, Aerospike) 
• Proven experience with distributed systems, data streaming, complex event Processing, NoSQL solutions for creating and managing data integration pipelines for batch and Real Time data needs.   
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Experience in Azure is a plus  
• Good understanding of machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc.   
• Expertise in Big Data technologies such as Hadoop, Spark, HBase, Kafka