Join our team as a Lead Software Engineer in the Machine Learning and AI solutions space within Consumer & Community Banking at JPMorgan Chase. Responsibilities include developing secure production code, leading technical evaluations, and driving the use of new technologies. Required skills include Python, SQL, CI/CD, Github, and experience with machine learning algorithms and MLOPS.
Job Description
Join our team as a Full Stack Software Engineer and play a pivotal role in shaping the future of Machine Learning and AI solutions within the Consumer & Community Banking sector at JPMorgan Chase.
As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking, 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
- Good experience of various machine learning algorithms, including supervised and unsupervised learning, neural networks and reinforcement learning
- Solid experience with Python, SQL, CI/CD pipeline, Github, AWS or Azure or GCP required
- End-to-end working knowledge on how a machine learning product is built
- Familiarity with MLOPS and components in MLOPS ecosystem
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s)
- Proficiency in automation and continuous delivery methods
- 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.)
- Practical cloud native experience
Preferred qualifications, capabilities, and skills
- In-depth knowledge of the financial services industry and their IT systems
- Practical AWS or Azure cloud native experiences
- Experience with deploying applications using Docker, Kubernetes
- Experience in data streaming tools such as Kafka
- Experience with Generative AI and LLM's
Top Skills
Python
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