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Software Engineer 3
PayPalSan Jose, United Statesfull_timeVerifiedPosted 4 Jun 2024
💰 $176,000/yr($72,700/yr – $176,000/yr)
About the role
At PayPal (NASDAQ: PYPL), we believe that every person has the right to participate fully in the global economy. Our mission is to revolutionize commerce globally to make moving money, selling and shopping, personalized and secure.
Job Description Summary:
What you need to know about the role:We are hiring talented and creative ML engineer for AIML platform team based in San Jose CA, you will be customer-centric, strategic & analytical in decision making and laser-focused on executing at scale. You thrive on the challenge of building and optimizing platforms at scale, are deeply passionate about leveraging cutting-edge technologies, and are dedicated to innovation and market success. You will have a chance to work on solving real world problems and gain practical experience in end to end Machine Learning life cycle. You will design, build, and optimize the platform for ML pipeline and data infrastructure. Additionally, you will gain domain expertise in a variety of industries, working with data scientists, researchers, and engineers to build ML models used across all PayPal domains.
Meet our Team:
PayPal AI/ML Platform is responsible for building the ML platform to help data scientists with the end-to-end model development lifecycle. We build state of the art and innovative ML infrastructure to support key product functions such as Fraud risk, Compliance, Personalization, Recommendations, Customer success, and other domains across PayPal.
Job Description:
Your way to impact -
- Strong critical thinking and problem-solving skills with the ability to address complex technical and non-technical challenges.
- Ability to influence at all levels of the organization and across multiple domains.
- Ability to lead complex technical and data science discussions and engagements that involve multiple personas including data scientists, data engineers, analysts and developers.
Your day-to-day
- Design and develop highly scalable and efficient platform that enables data scientists to build, deploy, and monitor machine learning solutions end-to-end.
- 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.
- Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner.
- Mentor team members, provide technical guidance, and foster a culture of collaboration, innovation, and continuous learning.
- Explore state-of-the-art deep learning techniques and Partner with data science and domain engineering teams to support the business transformation through AI.
- Develop trusted partnership with business, product, data scientists and architecture leaders to drive optimized platform product delivery
What do you need to bring
Qualifications:
- Solid track record of over-achieving engineering and platform delivery and scaling targets in high volume, innovative and fast-paced high-pressure environment; 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.
- Expertise in programming languages such as Python, Go, Java, and proficiency in machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc.
- 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.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
- Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner
- Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential.
- Experience with Jupyter Notebook, Kubeflow, Airflow, Argo, GPU and HPC
- Experience building ML infrastructure or MLOps platforms and Bigdata platforms technologies such as Hadoop, BigQuery, Spark, Hive and HDFS
Additional Job Description:
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