Data Architect
Location: Columbus OH
Required Skills : AWS Sagemaker... experience with Metaflow or something similar like MLFLow or Airflow etc. This person will be migrating their models from AWS Sagemaker. Python.
Responsibilities
- Build and maintain secure scalable infrastructure for ML model training testing and deployment using open-source tools.
- Create reusable deployment templates that standardize the path to production across teams.
- Translate prototype models into resilient monitored and observable production systems.
- Implement guardrails and controls that ensure compliance with internal standards (e.g. SR 11-7 ISO 42001).
- Partner with data scientists to simplify onboarding to platform capabilities.
- Establish CI/CD pipelines with hooks for testing scanning and validation of model code and artifacts.
- Serve as a technical lead for cross-functional delivery efforts involving model onboarding and platform integration.
Required Qualifications
- 6 years of experience in software data or ML engineering roles.
- Strong hands-on experience with tools like MLflow Metaflow Airflow or similar orchestration frameworks.
- Production experience with Kubernetes Docker and Helm.
- Deep understanding of Python and software engineering best practices.
- Experience implementing CI/CD pipelines and infrastructure-as-code in a cloud or hybrid environment.
Preferred Qualifications
- Experience working in regulated industries or environments with strong risk and compliance expectations.
- Familiarity with open-source model monitoring drift detection or lineage tools (e.g. Evidently AI Feast LakeFS).
- Hands-on experience serving models using KServe Ray Serve or Triton Inference Server.
- Familiarity with enterprise security tools like Trivy Aqua or Snyk for code and container scanning.
- Exposure to LLM/RAG architecture or GenAI platform integration.