We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Python Lead Software Engineer at JPMorgan Chase within the Corporate Sector, Engineering Enablement team, you are 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

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems 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 Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Advanced in one or more programming language(s) including Python and AWS Proficient use of AWS (Amazon Web Services) with experience with different type of database technologies and ability  to explain architectural specs, from a technical perspective. Working knowledge of creating AWS pipelines for ingestion, dataset creation, data transformation and model training.  Advanced knowledge of Statistics, Data Science and Machine Learning techniques. (supervised and unsupervised) Expertise using Scikit Learn, Pandas, TensorFlow, Keras, Spark, and NLTK for data mining and machine learning Ability to develop models for malware detection and malware family classification (Tensorflow/Keras, Sagemaker, AWS). Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Preferred qualifications, capabilities, and skills Python, R, Java, C, C++, SQL, SDLC process and tools (GIT, Jenkins, Artifactory etc )