Software Engineer III - ML Model Delivery
JPMorgan Chase7 hours ago
Responsibilities
- Design, build, and maintain platform components for the complete ML model lifecycle, including development, training, deployment, serving, and monitoring.
- Develop and maintain production data and feature pipelines that feed ML models.
- Build and manage AWS cloud infrastructure, including Databricks, EMR, ECS, and S3, for model training and serving workloads.
- Automate model deployment, testing, and release processes within the MLOps and SDLC toolchain.
- Support zero-downtime migration of legacy ML workloads to scalable, cloud-native platforms.
- Monitor platform health and model-serving infrastructure and resolve performance and stability issues.
- Use and validate enterprise-authorized AI-assisted development tools for coding, testing, troubleshooting, refactoring, documentation, and automation.
- Collaborate with data scientists and model developers to translate requirements into reliable platform capabilities.
- Contribute to secure coding, responsible AI use, resiliency, diversity, inclusion, and continuous improvement practices.
Requirements
- Formal training or certification in software engineering and at least 3 years of applied experience.
- Hands-on experience building and maintaining production data or ML pipelines.
- Hands-on experience using enterprise-authorized AI-assisted software development tools and critically evaluating their outputs.
- Understanding of responsible AI engineering workflows, data sensitivity, secure input and output handling, resiliency, and security expectations.
- Proficiency in Python and experience with ML libraries and frameworks such as Pandas, NumPy, and Scikit-learn.
- Working knowledge of AWS and cloud-native development patterns.
- Practical experience with infrastructure-as-code and deployment automation; Terraform is preferred.
- Ability to work independently on platform problems with moderate oversight.
- Preferred experience with Databricks, MLOps practices, model versioning, experiment tracking, feature stores, and model monitoring.
- Preferred exposure to RAG architectures, GenAI or LLM integration patterns, Docker, ECS, Kubernetes, AWS certifications, and Spark.
Benefits
- Competitive total rewards package and role-based benefits eligibility.
- Comprehensive health care coverage, on-site health and wellness centers, retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching.
- Eligible roles may include commission-based pay or discretionary incentive compensation.
- Equal opportunity employer with reasonable accommodation support.
Tech Stack
Categories
Data EngineeringML Engineering
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.