Principal Machine Learning Engineer - AI

PayPal - Austin, TX

Full-time - Senior

Austin, TX

Credit Intermediation and Related Activities

About the position

As a technical lead in PayPal's Enterprise AIML platform team, you will be customer-centric, strategic, and analytical in decision-making, with a strong focus on executing at scale. This role is pivotal in building and optimizing platforms that enhance the customer experience. You will leverage your extensive technical expertise and practical experience in AI/ML to lead discussions with technical and data science teams, guiding them through functional definition, architecture, solution implementation, and integration within complex environments. Your proven track record in technical leadership will be instrumental in driving high-quality products and ensuring the successful delivery of projects while effectively mentoring team members. In this position, you will be responsible for leading the design and deployment of scalable generative AI solutions and productizing ML models that enhance PayPal's ability to provide a seamless customer experience. You will ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. Additionally, you will drive innovation by researching and incorporating state-of-the-art machine learning techniques, tools, and frameworks into the platform. Effective communication and interpersonal skills are essential, as you will need to convey important messages clearly and compellingly while mentoring team members and fostering a culture of collaboration and continuous learning. Your role will also involve staying up to date with the latest advancements in AI/ML technology and industry trends, leveraging this knowledge to enhance the platform's capabilities. As one of the most senior engineers in the team, you will be the go-to person for any technical issues and decisions internally, partnering with other teams and representing the AIML team within a globally distributed organization.

Responsibilities

• Lead the design and deploy scalable generative AI solutions and productize ML models that enhance PayPal's customer experience.
• Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices.
• Drive innovation by researching and incorporating state-of-the-art machine learning techniques, tools, and frameworks into the platform.
• Mentor team members, provide technical guidance, and foster a culture of collaboration, innovation, and continuous learning.
• Stay up to date with the latest advancements in AI/ML technology and industry trends and leverage this knowledge to enhance the platform's capabilities.

Requirements

• Solid track record of over-achieving engineering and platform delivery and scaling targets in high volume, innovative, and fast-paced high-pressure environments; proven results in delivery on platform products.
• 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.
• Strong proficiency in machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models.
• Expert in multiple programming/scripting languages, i.e., Unix/Linux Shell Scripting, Python, Java, Scala.
• Expertise in Big Data technologies such as Hadoop, Spark, HBase, Kafka.
• Proficiency in SQL, ETL, database design.
• Good understanding of NoSQL databases like HBase, Redis, Aerospike.
• Good understanding of distributed systems, data streaming, complex event processing, NoSQL solutions for creating and managing data integration pipelines for batch and real-time data needs.
• Expertise in machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).

Nice-to-haves

• Experience in Azure is a plus.

Benefits

• Flexible work environment
• Employee shares options
• Health and life insurance
• Annual performance bonus
• Equity compensation
• Medical, dental, and vision benefits.