JPMorgan Senior Lead Software Engineer - Machine Learning 

United States, New Jersey, Jersey City 

795650817

In this role, you’ll define, build and evolve the infrastructure required to run batch and real time models, and to maintain pipelines for model training, batch/real-time model serving, hyperparameter tuning at scale, model monitoring, production validation and other activities vital for model development, testing and deployment in a well-managed, controlled environment.

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, opportunity, 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) : Python
• Experience and passion in model training, build, deployment and execution ecosystem such as Sagemaker and MLOps libraries such as Ray is needed
• Experience in monitoring and observability tools to monitor model input/output and features stats
• Experience and interest in ML model architectures. For example in linear/logistic regression, Gradient Boosted Trees, Neural Network architectures
• Ability to tackle design and functionality problems independently with little to no oversight
• Experience in containers (docker ecosystem), container orchestration systems [Kubernetes, ECS], DAG orchestration [Airflow, Kubeflow etc]
• Experience with cloud technologies like EC2, Sagemaker, IAM
• Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field

Preferred qualifications, capabilities, and skills

• Experience building high-throughput, low-latency micro service development leveraging AWS services such EKS, ECS, Fargate, etc.
• Advanced skills in MLOps.
• Hands-on experience with public cloud systems - AWS preferred
• Experience with recommendation and personalization systems
• Developing software in a well-managed SW dev environment such as Banking
• Good knowledge of database