Sr Engineering Manager, AI/ML Solutions

Company:  PayPal
Location: Austin
Closing Date: 07/11/2024
Salary: £100 - £125 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness.

Job Description Summary:

As a Senior Engineering Manager in PayPal’s Enterprise AIML platform team, you will be leading a team to build our Next Generation Recommendation Engine. Your role will involve leveraging your extensive technical expertise and practical experience in AI solutions to lead substantive discussions with technical and data science teams, guiding them through the intricacies of functional definition, architecture, solution implementation, and integration within complex environments.

Your day-to-day:

  • Provide technical leadership & manage a high-performing engineering team to build and scale our next generation recommendation engine.
  • Hire and directly lead a diverse team of top-tier ML and software engineers, taking charge of all facets of AI Products.
  • 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.
  • Collaborate with cross-functional teams including product managers, data scientists, and software engineers to define platform requirements and priorities.
  • Develop and evolve engineering processes and collaboration models to optimize team efficiency and collaboration.
  • 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.

What do you need to bring:

  • Proven experience in leading or managing machine learning/AI teams, with a track record of building successful AI solutions.
  • Solid track record of over-achieving engineering and platform delivery and scaling targets in a high-pressure environment.
  • Masters / bachelor’s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines.
  • Strong proficiency in machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models.
  • Proficiency in multiple Programming/scripting languages, i.e. Unix/Linux Shell Scripting, Python, Java, Scala.
  • Expertise in building data pipelines with Big Data technologies such as Hadoop, Spark, HBase, Kafka.
  • Proficiency in SQL, ETL, database design.
  • Experience with 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).
  • Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members.

PayPal is committed to fair and equitable compensation practices. Actual Compensation is based on various factors including work location and relevant skills and experience.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office and 2 days at your choice of either the PayPal office or your home workspace.

Commitment to Diversity and Inclusion:

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law.

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