We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer III at JPMorgan Chase within the Consumer and Community Banking, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

 

Deploy and maintain infrastructure (e.g., Sagemaker Notebooks) for providing an effective model development platform for data scientists and ML engineers that integrates with enterprise data ecosystem  Build, deploy and maintain ingress/egress and feature generation pipelines to calculate input features for model training and inference  Deploy and maintain infrastructure for batch and real-time model serving, in high throughput, low latency applications, at scale.  Identify, deploy and maintain high quality model monitoring and observability tools Deploy and maintain infrastructure for compute intensive tasks such as hyperparameter tuning and interpretability and explainability Partners with product, architecture, and other engineering teams to define scalable and performant technical solutions.        Leverages deep technical expertise to design extensible and scalable solutions, and to coach and grow individuals and teams. Ensures team executes work according to compliance standards, SLAs, and business requirements, to meet the objectives of an initiative.  Anticipates the needs of broader teams and potential dependencies with other teams.  Identifies and mitigates issues to execute a book of work while escalating issues as necessary. Proactively helps maintain high operational excellence standards for our production systems.  Encourages development of technological methods and techniques within team.

 

 

Required qualifications, capabilities, and skills

 

Formal training or certification on software engineering concepts and 3+ years applied experience Deep experience and passion in model training, build, deployment and execution ecosystem such as Sagemaker and/or Vertex AI  Experience in monitoring and observability tools to monitor model input/output and features stats Operational experience in big data tools such as Spark, EMR, Ray Experience and interest in ML model architectures - linear/logistic regression, Gradient Boosted Trees, Neural Network architectures Solid grounding in engineering fundamentals and analytical mindset Bias for action and iterative development Experience with recommendation and personalization systems. Programming languages: Python, some Java Solid fundamentals and experience in containers (docker ecosystem), container orchestration systems (Kubernetes, ECS), DAG orchestration (Airflow, Kubeflow etc.)

 

 

Preferred qualifications, capabilities, and skills

 

Solid fundamentals and experience with cloud technologies—EC2, Sagemaker, IAM Good knowledge of Databases