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We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As an Applied AI ML Lead at JPMorgan Chase within the Commercial and Investment Bank's AI for Technology team, youare an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job Responsibilities
Required qualifications, capabilities, and skills
Preferred qualifications, capabilities, and skills
JPMorgan Chase Bank, N.A., doing business as Chase Bank or often as Chase, is an American national bank headquartered in New York City, that constitutes the consumer and commercial banking subsidiary of the U.S. multinational banking and financial services holding company, JPMorgan Chase. The bank was known as Chase Manhattan Bank until it merged with J.P. Morgan & Co. in 2000.Chase Manhattan Bank was formed by the merger of the Chase National Bank and the Manhattan Company in 1955.The bank merged with Bank One Corporation in 2004 and later acquired the deposits and most assets of Washington Mutual.
Job ID: 142942739
Skills:
Machine Learning, Scipy, Data Mining, Tensorflow, Docker, Python, AWS, Natural Language Processing, Data Structures, Emr, Numpy, Algorithms, ECS, Pytorch, Time Series Analysis, Spark, Information Retrieval, Keras, Kubernetes, Computer Vision, Scikit-Learn, Sagemaker, MXNet, pyG, Ranking and Recommendation, Speech Recognition, Statistics, reinforcement learning, Knowledge Graph
Skills:
Pytorch, MLops, Python, cloud platforms, prompt engineering
Skills:
Computer Vision, Emr, Numpy, Information Retrieval, ECS, Data Structures, Keras, Natural Language Processing, Data Mining, Algorithms, Machine Learning, Time Series Analysis, AWS, Tensorflow, Kubernetes, Python, Scipy, Docker, Pytorch, Spark, Scikit-Learn, Sagemaker, Knowledge Graph, MXNet, Statistics, pyG, reinforcement learning, Ranking and Recommendation, Speech Recognition
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