Senior Data Platform Engineer – ModelOps

Digi-Key Electronics; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Digi-Key Electronics is seeking an experienced professional for a role focused on building and maintaining end-to-end ML pipelines in Bengaluru, Karnataka. The ideal candidate will have 5 to 7 years of IT experience, specifically in Model Ops, and must demonstrate strong Python and software engineering skills.

Responsibilities include implementing CI/CD pipelines, operationalizing GenAI systems, and establishing monitoring for model performance. If you thrive in a collaborative environment and are eager to contribute to internal platform standards, we encourage you to apply.

Qualifications

• 5 to 7 years of overall IT experience with 3+ years in Model Ops.
• Strong Python and software engineering practices required.
• Experience deploying ML systems in batch and real-time environments.

Responsibilities

• Build and maintain end-to-end ML pipelines.
• Implement CI/CD pipelines for ML workflows.
• Operationalize GenAI systems and establish monitoring.

Skills

Python

Docker and Kubernetes

CI/CD pipelines

Model Ops

Monitoring/alerting systems

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Dataiku DSS

Azure DevOps

GitHub Actions

Job description

About DigiKey

DigiKey is one of the fastest growing distributors of electronic components in the world. Since its founding in 1972, DigiKey has been committed to offering the broadest selection of in‑stock electronic components, as well as providing the best service possible to its customers, aiding engineers through the entire design process, from Prototype to Production. This has led the company to be highly ranked year after year in industry surveys in North America as well as Europe and Asia, in categories covering such facets of business as availability of products, speed of service, responsiveness to problems, and more.

Key Responsibilities

• Build and maintain end‑to‑end ML pipelines (train → validate → deploy → monitor)
• Productionize models for batch scoring (scheduled pipelines) and real‑time APIs (Kubernetes‑hosted services)
• Standardize deployments using Dataiku (Automation + API nodes) and containerized services on Azure Kubernetes Service (AKS)
• Implement CI/CD pipelines (Azure DevOps/GitHub Actions) for ML workflows
• Establish monitoring and alerting for model performance, drift, failures, and 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 and software engineering practices (testing, Git, modular code)
• Experience deploying ML systems in batch and real‑time environments
• Hands‑on with Docker and 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, 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)