Applied AI/ML Associate

JPMorgan Chase & Co.Houston, TX
10h

About The Position

Join and be a part of ML Engineer/Software Eng. to design, build, deploy, and operate production-grade ML Applications. As an ML Engineer/Software Engineer within the team, you will design, build, deploy, and operate production-grade machine learning services. You will partner closely with Data Scientists to industrialize models, build Python-based model wrappers, manage Kubernetes-based runtime (GKP) in UAT and Production, and ensure reliable CI/CD for model hosting packages. This role also coordination with other technology team, task planning, and mentoring team members.

Requirements

  • Strong Python software engineering skills (OOP, packaging, dependency management, virtual environments) and testing (pytest, mocking, coverage).
  • Hands-on Kubernetes cloud based experience operating services in UAT/Production (deployments, pods, jobs/autosys, liveness/readiness probes, autoscaling, logs, and metrics).
  • Experience building and releasing production ML services (model packaging, API serving, model/version management).
  • CI/CD experience (e.g., Jenkins, GitLab CI, GitHub Actions, Spinnaker) for automated builds, tests, security scans, and multi-environment deployments.
  • Proficiency with Oracle SQL and performance tuning for model-serving and batch workloads.
  • Solid Linux fundamentals, shell scripting, Git workflows, and code review practices.
  • Observability and operational ownership with experience responding to and preventing production incidents.
  • Excellent communication and collaboration skills, with a track record of working alongside Data Scientists and coordinating multi-team projects.
  • Demonstrated ability to plan own work, manage one's schedule, and drive one's execution across concurrent initiatives.

Nice To Haves

  • MLOps tooling experience (e.g., MLflow, Airflow, Kubeflow, feature stores, model registries, drift monitoring)
  • Data engineering at scale (Spark/Databricks), streaming (Kafka), and batch orchestration.
  • Infrastructure-as-Code (Terraform), artifact and container management, and container hardening.
  • Familiarity with model governance, validation, and audit requirements in regulated environments.
  • Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent experience).

Responsibilities

  • Build robust Python model wrappers and service interfaces that standardize inference, logging, and telemetry for multiple ML models.
  • Develop and maintain ML pipelines for packaging, testing, and deployment across UAT and Production, including versioning and rollback strategies.
  • Operate and maintain GKP Kubernetes pods and scheduled jobs in UAT and Production, including configuration, scaling, resource quotas, secrets, and monitoring.
  • Own model host package builds and deployments through CI/CD, including promotion workflows, environment configuration, and change management.
  • Troubleshoot and resolve UAT and Production issues end-to-end (application, model, data, infrastructure), performing root-cause analysis and implementing fixes, including model updates as needed.
  • Partner with Data Scientists during model development to integrate feature code, create reusable Python libraries, write unit tests, perform code reviews, and improve reproducibility.
  • Engineer performant data access for model inference and batch jobs against Oracle Database (SQL optimization, schemas, stored procedures) and support data pipeline needs.
  • Establish and enforce operational excellence practices: health checks, observability, alerting, SLOs/SLAs, security baselines, and documentation.
  • Participate in scrum ceremonies and the agile process
  • Coach and assist team members to remove blockers, share best practices, and elevate code quality and delivery efficiency.

Benefits

  • 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.
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