Are you ready to make a significant impact in the world of AI and machine learning? At JPMorgan Chase, In this role, you'll be a key player in an agile team dedicated to enhancing, building, and delivering market-leading technology products that are secure, stable, and scalable

As a Software Engineer III/Machine Learning Engineer, at JPMorgan Chase within the Corporate Sector – AIML Data Platforms Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

 

Job responsibilities

Implements distributes ML experimentation and training platform for firm-wide use in accordance with the requirements and design.Implements, and supports tools and workflows to facilitate machine learning experiments, automated training runs, and production deployments.Extends machine learning libraries and frameworks to support complex requirements.Delivers thoughtful data scientist experience with APIs and SDKs for the training platform.Collaborates with infrastructure engineering, product management, and security and compliance teams to deliver tailored, robust solutions.

 

Required qualifications, capabilities, and skills

Formal training or certification on software engineering  concepts and 3+ years applied experienceKnowledge of software development processes in an ML environment.Understanding and hands-on experience with public cloud technologies, especially with AWS (Azure would be a plus), in the context of ML engineering workflows, specifically featurization, experimentation, training, and evaluation.Programming skills in Python and experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, JAX, etc.Hands-on experience implementing DevOps practices using tools such as Docker, Jenkins, Spinnaker, and Terraform.Knowledge of Big Data and related technologies such as Hadoop, Spark, and Airflow.

Preferred qualifications, capabilities, and skills

Knowledge of SageMaker, EMR, and AWS ML stack.Knowledge of Kubernetes ecosystem, including EKS, Helm, and Custom Operators.