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Senior Data Platform Engineer – ModelOps

DigiKey
Karnataka, IND
Full-time
Senior · 16+ years experience
Hybrid
Discovered 2 weeks ago
azuredatadogdockergitgithub-actionskubernetes

Full Job Posting

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)
  • Standardize deployments using:
  • 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
  • Operationalize GenAI systems (LangChain/RAG):
  • Prompt/version control, evaluation pipelines, tracing, cost controls
  • Define and enforce model governance:
  • 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
  • Collaboration & Support
  • Act as the primary platform contact for Model Ops.
  • Provide support and participate in incident response and root-cause analysis.
  • Mentor junior engineers to enable L1/L2 support and contribute to internal platform standards.

Preferred Qualifications

  • Dataiku DSS (Automation node, API node, scenarios)
  • Azure services (ML, Storage, Key Vault, Monitor)
  • MLflow or model registry experience
  • LangChain / RAG / vector databases
  • Observability tools (Monte Carlo, Langsmith, Datadog or equivalents)
  • All personal data collected will be used for recruitment purposes only. All unsuccessful applications will be deleted within 24 months.
  • Hands-on with Docker + Kubernetes (AKS preferred)

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