Location: Plano, TX, United States

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer III at JPMorgan Chase within Enterprise Technology, you are an individual contributor who should be able to apply quantitative, data science and analytical skills to complex problems. You’re able to work across teams to design, develop, and evaluate and execute against those data science and analytical solutions with a keen functional understanding of the business problem. You will be responsible for data wrangling, data analysis, modeling, including model selection and producing quick applicable modeling solutions.

Job responsibilities

• Engaging with stakeholders and understanding business requirements,
• Develops secure high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Developing AI/ML solutions to address impactful business needs,
• Working with other team members to productionize end-to-end AI/ML solutions,
• Engaging in research and development of innovative relevant solutions,
• Collaborating with other teams across the firm to attain the mission and vision of the team and the firm

Required qualifications, capabilities, and skills 

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• Advanced degree in analytical field (e.g., Data Science, Computer Science,  Engineering,  Applied Mathematics, Statistics, Data Analysis,  Operations Research)
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Experience in the application of AI/ML to a relevant field,
• Practical cloud native experience
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated practical experience in machine learning techniques, supervised, unsupervised, and semi-supervised.
• Strong experience in natural language processing (NLP) and its applications.
• Solid coding level in programming languages including  Python and  experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects.