Software Engineer III - ML Pipelines(Python, Pyspark , AWS)
JPMorgan Chase18 hours ago
Responsibilities
- Design, build, and maintain platform components supporting the end-to-end ML model lifecycle.
- Develop and maintain production data and feature pipelines for ML models.
- Build and manage AWS infrastructure, including Databricks, EMR, ECS, and S3, for model training and serving.
- Automate model deployment, testing, and release processes within the SDLC and MLOps toolchain.
- Migrate legacy ML workloads to scalable cloud-native platforms with zero downtime.
- Monitor model-serving infrastructure and resolve performance and stability issues.
- Drive team adoption of approved AI-assisted engineering tools while establishing standards for secure coding, peer review, automated testing, and validation of AI outputs.
- Collaborate with data scientists and model developers to translate requirements into reliable platform capabilities.
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.
- Experience leading effective use of approved AI-assisted software development tools and validating their outputs for correctness, performance, and security.
- Knowledge of responsible AI use, data sensitivity, secure input and output handling, resiliency, and security expectations.
- Proficiency in Python and experience with Pandas, NumPy, Scikit-learn, or similar ML libraries and frameworks.
- Working knowledge of AWS and cloud-native development patterns.
- Experience with big data processing frameworks, with Spark preferred.
- Practical experience with infrastructure-as-code and deployment automation, with Terraform 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 AWS certifications, such as Solutions Architect Associate.
- Exposure to RAG architectures or GenAI/LLM integration patterns.
- Knowledge of container-based deployment using Docker, ECS, or Kubernetes.
Benefits
- Competitive total rewards and benefits package, with additional compensation details provided during the hiring process.
- Comprehensive health care coverage and on-site health and wellness centers.
- Retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching.
- Equal opportunity employer offering reasonable accommodations for religious practices, mental health needs, and disabilities.
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.