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JPMorgan Chase (JPMC) is a leading global financial services firm with assets of $2 trillion and operations in more than 60 countries. JPMC has made a strategic decision to fundamentally transform its operations through the adoption of artificial intelligence and machine learning at scale. We are the AI Acceleration (AIX) team, a new group headquartered in Palo Alto, tasked with achieving this vision. We're hiring the best of the best from Silicon Valley to come join us. You will join the AI Engineering team and work alongside other leaders who have built and shipped AI and Machine Learning products at Google, Facebook, Microsoft, and Salesforce.
Responsibilities * Collaborate with all of JPMorgan's lines of business and functions to deliver software solutions. * Research, design, and build new features, end to end on our new AI platform which will accelerate the productivity of all data scientists and researchers working at JPMorgan. * Work with a variety of open source technologies, combined with internal systems and platforms to deliver an innovative, best in class AI platform. * Build new features in the AI platform to facilitate model training, evaluation, deployment and monitoring. * Implement algorithms and data visualizations for model explainability and interpretability. * Evaluate various cloud platform technologies for big data and machine learning tasks. Architect and build features in the platform to incorporate these systems. * Leverage the team's knowledge of the data science process to design and build end to end workflows customized to JPMorgan's requirements. * Determine the suitability of various open source AI and ML libraries for large scale distributed model training on structured and unstructured data sets. * Build scalable and testable automated systems for big data pipelines and scheduled training job requests. * Work with the model risk governance teams to build processes and tools to expedite the verification of models and production deployment. * Design and build UI and backend processes for a machine learning dashboard to facilitate platform monitoring and collaboration between data scientists.
Preferred Qualifications * Some knowledge in Machine Learning, Data Mining, Information Retrieval, Statistics. * Big data technologies: Hadoop, Hive, Spark, Kafka. * Experience in ETL pipelines, both batch and real-time data processing. * Experience in distributed system design and development. * Major machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch, Keras, Scikit-Learn, H2O * General knowledge of machine learning platforms: SageMaker, Kubeflow, Domino, DataRobot, DriverlessAI
Internal Number: 6509976
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