JPMorgan Lead Software Engineer Machine Learning & Cloud 

United States, Delaware, Wilmington 

998423568

Job responsibilities

• Design Enterprise Machine Learning platforms that are capable of running predictive models
• Provides Technical Leadership, guidance and direction to other team members
• Writes secure and high-quality code using the syntax of at least one programming language with python, Java
• Establish standards, guidance and best practices for the technical aspects in the team
• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
• Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
• Leverages Cloud services to build ML pipeline to implement, deploy and produce Machine Learning Models
• Work with Business stakeholders and Product Owners to understand requirements.
• Work with Site Reliability Engineer for any infrastructure/production changes.
• Ingests data from multiple sources

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Attitude to learn new technologies. Passionate about building an innovative culture
• Experience in programming languages such as Python/Java.
• Understands/learn the basic architecture of Cloud services and usage.
• Background with Machine Learning Frameworks and Big Data technologies such as Hadoop, Hive.
• Experience working with databases such as Oracle or Cassandra.
• Exposure to Agile and scrum methodologies.
• Familiarity with CI/CD, Application Resiliency, and Security.
• Emerging knowledge of software applications and technical processes within any technical discipline such as cloud, artificial intelligence, machine learning, Data analytics.

• Knowledge of any of the technologies like Big Data / Distributed computing like Spark, Kafka, Terraform, Kubernetes, AWS.
• Python Machine Learning library and ecosystem experience (Pandas and Numpy etc.)