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Senior Data Platform Engineer – ModelOps
Digikey
IND
Full-time
Senior · 5+ years experience
Hybrid
Discovered 3 weeks ago
PythonGitDockerKubernetesGitHub ActionsDataiku DSS
Free
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PythonGitDocker
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PythonGitDockerKubernetesGitHub ActionsDataiku DSS
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Key Responsibilities
- Build and maintain end-to-end ML pipelines (train → validate → deploy → monitor)
- Productionize models for: Batch scoring (scheduled pipelines) Real-time APIs (Kubernetes-hosted services)
- Batch scoring (scheduled pipelines)
- Real-time APIs (Kubernetes-hosted services)
- Standardize deployments using: Dataiku (Automation + API nodes) Containerized services on Azure Kubernetes Service (AKS)
- Dataiku (Automation + API nodes)
- Containerized services on Azure Kubernetes Service (AKS)
- Implement CI/CD pipelines (Azure DevOps/GitHub Actions) for ML workflows
- Establish monitoring and alerting: Model performance, drift, failures, latency
- Model performance, drift, failures, latency
- Operationalize GenAI systems (LangChain/RAG): Prompt/version control, evaluation pipelines, tracing, cost controls
- Prompt/version control, evaluation pipelines, tracing, cost controls
- Define and enforce model governance: Model registry, approvals, auditability, documentation
- Model registry, approvals, auditability, documentation
- Build reusable templates and “paved roads” for data scientists
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field (16 years of formal education).
- 5 to 7 years of overall IT experience with 3+ years in Model Ops
- Strong Python + software engineering practices (testing, Git, modular code)
- Experience deploying ML systems in batch and real-time environments
- Hands-on with Docker + Kubernetes (AKS preferred)
- Experience with CI/CD pipelines (Azure DevOps or GitHub Actions)
- Experience implementing monitoring/alerting for production systems
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