Job
Description
As a Lead Software Engineer- ML at JPMorgan Chase within the Trust & Safety, Payments Technology organization, you will play a pivotal role in an agile team that is committed to enhancing, creating, and delivering high-quality technology products in a secure, stable, and scalable way. Your technical skills and contributions will greatly influence the business, and your comprehensive technical knowledge and problem-solving strategies will be utilized to tackle a broad spectrum of challenges across diverse technologies and applications. Job responsibilities Writes advanced level code in Python to build cutting edge AI/ML engineering solutions. Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors. Develops secure and high-quality production code, and reviews and debugs code written by others. Drives decisions that influence the product design, application functionality, and technical operations and processes. Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle Influences peers and project decision-makers to consider the use and application of leading-edge technologies. Adds to the 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 building low latency, high throughput server side python based software solutions. Proficiency with AIM algorithms. Advanced hands on experience in Python and or Java programming language(s) Practical experience in ML engineering & MDLC Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (eg, cloud, artificial intelligence, machine learning, mobile, etc) Ability to tackle design and functionality problems independently with little to no oversight. Practical cloud native experience one or more public clouds AWS, GCP, MS Azure Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field Experience with modern microservices architecture Knowledge of Cloud Native Technologies (Docker, Kubernetes, Kafka, etc). Preferred qualifications, capabilities, and skills Expertise in application, data, and infrastructure architecture disciplines Experience with Cassandra or equivalent no-SQL databases Experience with Agile development Excellent verbal and written communication
