
Software Engineer III - ML Model Delivery
Required skills
- Python
- Pandas
- NumPy
- Scikit-learn
- AWS
- Databricks
- EMR
- ECS
- S3
- Terraform
Nice to have
- MLOps
- model versioning
- experiment tracking
- feature stores
- model monitoring
- RAG architectures
Role summary
JPMorgan Chase is seeking a Software Engineer III specializing in ML Model Delivery to join their agile Risk Technology team. This role involves designing, building, and maintaining platform components for the end-to-end ML model lifecycle, including development, training, deployment, and monitoring. The engineer will leverage AI-assisted development tools, build and manage cloud infrastructure on AWS, and develop data/feature pipelines. Responsibilities also include automating deployment processes, supporting legacy workload migration, monitoring platform health, and collaborating with data scientists. A strong foundation in Python, ML libraries, AWS, and infrastructure-as-code is required, with preferred experience in MLOps, containerization, and Big Data frameworks.
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 - Risk Technology Portfolio team, you will be part of an agile team that builds and delivers trusted technology products in a secure, stable, and scalable way. You will take ownership of technical deliverables, contribute to design decisions, and work across cloud, data, and machine learning domains to solve real business problems.
Job Responsibilities:
- Design, build, and maintain platform components that support end-to-end ML model lifecycle — from development and training to deployment and monitoring
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
- Develop and maintain data and feature pipelines that feed ML models in production
- Build and manage cloud-based infrastructure on AWS (including Databricks, EMR, ECS, and S3) to support model training and serving workloads
- Automate model deployment, testing, and release processes within the SDLC/MLOps toolchain
- Support migration of legacy ML workloads to cloud-native, scalable platforms with zero downtime
- Monitor platform health and model serving infrastructure; identify and resolve performance and stability issues
- Apply AI-assisted development tools and best practices to improve code quality and delivery speed
- Collaborate with data scientists and model developers to understand requirements and translate them into reliable platform capabilities
- Contribute to a team culture of diversity, inclusion, and continuous improvement
Required Qualifications, Capabilities, and Skills:
- Formal training or certification in software engineering and 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 within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
- Proficiency in Python and experience with ML libraries and frameworks (Pandas, NumPy, Scikit-learn, etc.)
- Working knowledge of cloud platforms, particularly AWS, and cloud-native development patterns
- Practical experience with infrastructure-as-code and deployment automation (Terraform preferred)
- Ability to work independently on platform problems with moderate oversight
Preferred Qualifications, Capabilities, and Skills:
- Experience with Databricks for model training and data pipeline development
- Familiarity with MLOps practices — model versioning, experiment tracking, feature stores, and model monitoring
AWS certifications (e.g., Solutions Architect Associate) - Exposure to RAG architectures or GenAI/LLM integration patterns
- Knowledge of container-based deployment (Docker, ECS, or Kubernetes)
- Interest in AI-assisted engineering tools and automation within the SDLC
- Experience with Big Data processing frameworks (Spark preferred)
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You’ll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
Sample JPMorganChase interview questions
- 1
In a full stack application with high traffic, what would you do to make the application highly efficient?
system designdifficult - 2
Design Google Drive
system designmedium - 3
How would you troubleshoot a bug that only happens sometimes?
technicalmedium - 4
Difference between a hashmap and a hashlist
technicaldifficult - 5
If some of your REST endpoints are slow and not behaving normally, how would you diagnose the problem, and how would you fix it.
technicaldifficult
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