Applied AI ML Lead

Embark on a transformative journey with JPMorgan as we evolve into a technologically advanced, client-focused company. We're seeking top talent for our AI engineering team to integrate machine learning into our key products, working closely with our tech partners. This role, part of the Payments Trust & Safety Team, offers a unique opportunity to influence the financial services industry by developing impactful Machine Learning solutions. Join us in building next-gen technology that leverages JPMorgan's unique data and full-service advantage to create high-impact AI applications and platforms.

As a  Applied AI ML Lead within the Payments AI/ML team at JPMorgan, you will collaborate with all lines of business and functions to deliver software solutions. You will have the opportunity to research, experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant business impact. You will also design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to promote and optimize business results. You will hire and lead a team of ML scientists as we set out to solve impactful business problems at JPMC.

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: 

• MS with 10+ years of experience or PhD with 7+ years of experience and a 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