Join JPMorgan's Digital Intelligence team on our transformation journey into a client-centric, technology-promoten company. With a $10B+ tech budget, we're investing in next-gen infrastructure, data, and AI technology. We're seeking top talents for our AI engineering team to develop high-quality machine learning models, services, and scalable data processing pipelines. Candidates should have a strong computer science background and be ready to handle end-to-end projects, focusing on engineering.

As an Applied AI ML Lead within the Digital Intelligence team at JPMorgan, you will have the opportunity to collaborate with all lines of business and functions to deliver software solutions. You will experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant impact on technology and business. You will also design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to promote and optimize business results. This role provides an exciting opportunity to contribute to a transformative journey and make a substantial impact on a wide range of customer products.

Job Responsibilities:

Collaborate with all of JPMorgan’s lines of business and functions to delivery software solutions. Experiment, develop and productionize high quality machine learning models, services and platforms to make huge technology and business impact. Design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to drive and optimize business result.

Required qualifications, capabilities and skills:

BS, MS or PhD degree in Computer Science, Statistics, Mathematics or Machine learning related field. Solid programming skills with Java, Python or other equivalent languages. Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Expert in at least one of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Knowledge of machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, Scikit-Learn. Experience in ETL data pipelines both batch and real-time data processing, Data warehousing, NoSQL DB. Strong analytical and critical thinking skills. Self-motivation, great communication skills and team player.

 

Preferred qualifications, capabilities and skills :

Cloud computing: Google Cloud, Amazon Web Service, Azure, Docker, Kubernetes. Experience in big data technologies: Hadoop, Hive, Spark, Kafka. Experience in distributed system design and development