JPMorgan Senior Lead Software Engineer - ML/Data 

United States, New Jersey, Jersey City 

861541422

Job Responsibilities

• 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
• Serves as a function-wide subject matter expert in one or more areas of focus.
• 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 in Software Engineering and 5+ years of applied experience.
• Experience in building complex software systems in both private and public cloud environments (AWS).
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced in one or more programming language(s)
• Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, etc.)
• Ability to tackle design and functionality problems independently with little to no oversight.
• Practical cloud native experience
• Experience in Computer Science, Computer Engineering, Mathematics, or a related discipline.

Preferred qualifications, capabilities, and skills

• Proficiency in container and cloud technologies, including Docker, Kubernetes, and AWS.
• Hands-on experience in building ETL/Data Pipelines and data lake platforms, such as AWS Redshift, Glue, Databricks, Spark/Hadoop, and Snowflake.
• Familiarity with workflow orchestration tools like Apache Airflow and AWS Step Functions, as well as integration technologies like GraphQL and REST.
• Experience in building and deploying Machine Learning models, with practical knowledge of the ML Lifecycle. Expertise in MLOps and AIOps is a significant advantage.