As a Software Engineer III – MLOps at JPMorgan Chase as a part of Banking and Wealth Management Technology, you build and operate a machine learning operations (MLOps) platform on Amazon Web Services (AWS) that supports model development, CI/CD, deployment, monitoring, and governance across multiple environments
We are building a secure, resilient machine learning delivery ecosystem that helps teams move faster without compromising controls. In this role, you will develop platform foundations—Infrastructure as Code, Kubernetes patterns, multi-environment governance, and operational excellence—so product and data teams can deploy and operate models with confidence. You will collaborate across engineering, data, and risk partners to standardize best practices, strengthen reliability, and improve developer experience. The work spans build, run, and continuous improvement across multiple environments.
You will contribute to platform resiliency through high-availability designs, multi-Availability Zone patterns, capacity planning, and incident readiness. You will define observability standards to ensure services are measurable, diagnosable, and supportable in production. Your work will help teams deliver batch and online inference safely with standardized deployment and rollback approaches.
Job responsibilities
- Five years of experience in platform engineering, software engineering, or machine learning operations roles.
- Hands-on experience building and operating production platforms on AWS.
- Hands-on experience with Kubernetes, including Amazon EKS, Helm or Kustomize, ingress, autoscaling, and workload scheduling.
- Hands-on experience using Terraform for repeatable environment provisioning and controlled change management.
- Demonstrated experience using approved AI-assisted software development tools to support coding, code review, testing, troubleshooting, and documentation, with clear validation practices for correctness, performance, and security.
- Knowledge of responsible AI use in engineering workflows, including data sensitivity awareness and secure handling of inputs and outputs.
- Experience implementing security controls for cloud and Kubernetes platforms (for example: identity and access management, role-based access control, secrets management, network policies, and vulnerability management).
- Experience designing and operating highly available systems, including on-call readiness, incident response, and post-incident reviews.
- Experience establishing or operating observability practices across metrics, logs, traces, dashboards, alerting, and service-level objectives (where defined).
- Experience building and operating streaming pipelines with Apache Kafka and Apache Flink.
- Proficiency in one or more programming languages used in platform or streaming engineering (for example: Python, Java, Scala, or Go), plus CI/CD automation experience.
Required Qualifications, Capabilities, and Skills
- 5+ years (or equivalent) in platform engineering, Java, or MLOps roles.
- Hands-on experience building production platforms on AWS.
- Strong Kubernetes experience, including Amazon EKS, Helm/Kustomize, ingress, autoscaling, and workload scheduling.
- Strong Terraform experience for repeatable environment provisioning and change management.
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Experience implementing security controls for cloud/Kubernetes platforms (IAM, RBAC, secrets, network policies, vulnerability management).
- Proven ability to deliver resilient, highly available systems and to operate them (on-call readiness, incident response, postmortems).
- Strong observability experience (metrics/logs/traces, dashboards, alerting, SLOs).
- Streaming experience with Kafka and real-time data processing; experience building/operating Flink pipelines is required.
- Solid programming/scripting skills (commonly Python, Java/Scala for Flink, and/or Go) and CI/CD automation experience.
Preferred Qualifications
- Experience enabling GPU workloads on Kubernetes (for example: device plugins, node pools, scheduling, and performance tuning).
- Familiarity with machine learning platform components such as model registries, experiment tracking, feature stores, and artifact management.
- Experience with service mesh, policy as code, and container supply chain security.
- Experience integrating with data lake or data warehouse platforms and implementing data quality monitoring.
- Experience working in regulated environments with strong engineering governance.
About Us
Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
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.
Equal Opportunity Employer/Disability/Veterans
About the TeamOur Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.Similar Jobs
What you need to know about the Austin Tech Scene
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

