Bulge Bracket Investment Banks

Software Engineer III - Machine Learning Platform

at J.P. Morgan

Mid LevelNo visa sponsorshipPython

Posted 5 days ago

No clicks

Compensation: Not specified USD
City: Palo Alto
Country: United States

As a Software Engineer III within JPMorgan Chase's Consumer and Community Banking Technology team, you will design, build, and maintain scalable ML platform infrastructure to support end-to-end ML workflows. You will develop tools for model training, deployment, monitoring, and lifecycle management, and integrate data engineering, feature management, and model serving into unified platform solutions. The role emphasizes secure, reliable production code, automation, CI/CD, and collaboration with data scientists, ML engineers, and product teams to accelerate ML development. Responsibilities cover architecture, implementation, and ongoing optimization to improve platform reliability and performance.

Location: Palo Alto, CA, United States

Advance your career by building and optimizing cutting-edge machine learning platforms that empower data-driven innovation across JPMorgan Chase.

As a Software Engineer III at JPMorgan Chase within the Consumer and Community Banking Technology team, you will play a pivotal role in designing, developing, and maintaining robust infrastructure and tools that enable data scientists and ML engineers to efficiently develop, deploy, and monitor models. Leveraging your technical expertise and collaborative mindset, you will deliver secure, scalable, and reliable solutions that drive the firm’s business objectives and enhance ML platform capabilities. Your contributions will span the full software development lifecycle, from architecture and implementation to automation and continuous improvement. In this impactful role, you will help shape the future of machine learning at JPMorgan Chase.

Job Responsibilities

Design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows.

Develop and optimize tools for model training, deployment, monitoring, and lifecycle management.

Integrate data engineering, feature management, and model serving capabilities into unified ML platform solutions.

Implement secure, high-quality production code for platform services, APIs, and automation pipelines.

Collaborate with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations.

Ensure platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement.

Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.

Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services.

Contribute to the ML platform engineering community of practice and participate in events that explore new and emerging technologies.

Required Qualifications, Capabilities, and Skills

3+ years of applied experience or formal training/certification in software engineering concepts.

Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure.

Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL).

Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure.

Strong understanding of MLOps practices, including CI/CD for ML, model versioning, and monitoring.

Experience developing APIs and platform services for ML workflows.

Solid knowledge of the software development life cycle and agile methodologies.

Ability to collaborate with cross-functional teams to deliver platform solutions aligned with business objectives.

Preferred Qualifications, Capabilities, and Skills

Familiarity with Databricks for scalable data engineering and ML platform integration.

Experience working with Snowflake for cloud-based data warehousing and analytics.

Exposure to Snorkel AI for programmatic data labeling and training data management.

Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow).

Familiarity with feature stores, model registries, and ML metadata management.

Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).

Experience with RESTful APIs and microservices architectures.

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorgan Chase’s review of criminal conviction history, including pretrial diversions or program entries.

Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team

Back to all Python jobs