Staff Machine Learning Engineer
Chicago IL, Scottsdale AZ, Austin TX
At Venmo and PayPal, we are creating a product that people love. We strive to create a delightful user experience while connecting the world and empowering people through payments. We are looking for intellectually curious people who want to be inspired and inspire others to change the world. Engineering is a craft, and at Venmo we want the internals of our software to be as elegant as the end user experience we are designing. We spend our days scaling our capacities and building new features to meet and exceed our user’s needs and wants. We teach and learn from one another and push each other to be at our creative and analytical bests.
Product Intelligence team
Imagine what you could do here. Venmo is the fastest growing peer-to-peer financial brand and keeps innovating in the tech industry. The Venmo Product Intelligence (a.k.a Applied Science) team is looking for a talented Staff Machine Learning Engineer - Software to help build our next generation of data products and ML services. We derive valuable insights from our extensive, rich and rapidly growing datasets in order to improve the daily experience of our customers. This role is critical to the engineering team and will be deeply embedded within multi-disciplinary teams across the company.
You will join the team that partners with data scientists and data engineers to transform machine learning models into algorithm-driven services. You will have the opportunity to take full ownership of the design and implementation of highly reliable, scalable and performant services. You’ll contribute across the entire ML Ops lifecycle (including model training, deployment, and monitoring), building out tooling that enables data scientists to productionize their models. You will drive the adoption of appropriate technologies for business, lead the way for continuous innovation and shape the future of e-commerce.
5+ years of industry experiences in building software and services to support machine learning applications.
Extensive experience in building large-scale machine learning infrastructure for online recommendation, ads ranking, personalization, search, NLP, etc.
Experience with Big Data and distributed technologies such as Spark, EMR, Kafka.
Practical experience in object-oriented design, data structures, algorithm designs, run-time analysis and code quality verification.
Proficiency in at least one modern programming language such as Python (preferred), Scala, Java, etc.
Operational experience of AWS Lambda, Dynamo DB, Sagemaker, Personalize and other services.
Have a deep understanding of experimental design and architecture, preferably at scale.
Preferred to have a basic knowledge of machine learning and data science.
Passion and intellectual curiosity for the social science and FinTech domain.
Comfortable in working in an ambiguous, fast-paced and high-growth dynamic environment.
Excellent written and verbal communication, and ability to take ownership of meeting with cross-functional team leads on a regular basis.
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