ML Pipeline Engineer

5 days ago

Kollam, Kerala, India beBeeMloper Full time ₹ 18,00,000 - ₹ 25,00,000
Job Role

We are seeking a highly skilled Machine Learning Engineer to drive our model production, pipeline automation, and scalable solution development.

Key Responsibilities:

  • Own the productionization of models from tracked experiments to governed releases, ensuring resilient services with clear Service Level Objectives (SLOs), runbooks, and fast, safe rollbacks.
  • Build automation-first delivery pipelines using GitLab CI and Terraform-based Infrastructure as Code (IaC), focusing on reproducible builds, layered tests, and environment promotion.
  • Engineer scalable serving solutions for batch and real-time inference on Amazon Elastic Container Service for Kubernetes (EKS), Amazon Elastic Container Service (ECS), AWS Lambda, and Databricks Model Serving, incorporating probes, autoscaling, and canary/blue-green deployments.
  • Instrument end-to-end observability, detect drift/regressions, and lead incidents and post-mortems to drive durable fixes.
  • Partner across teams to translate requirements into designs, Architecture Decision Records (ADRs), and change plans, balancing security, privacy, cost, and performance tradeoffs.
  • Continuously reduce toil through automation, optimize model/GPU/LLM cost, and evolve templates/playbooks for repeatable delivery.

Requirements:

  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience as outlined in the key responsibilities; or High School Diploma/General Education Degree and 6+ years of relevant experience as outlined in the key responsibilities in lieu of Bachelor's Degree.
  • 3+ years operating ML systems in production (MLOps).
  • Experience with Python for ML engineering (packaging, typing, testing, performance)
  • Experience developing GitLab CI for ML/General Artificial Intelligence (GenAI) (multi-stage pipelines, artifacts, evaluation/security gates) and Terraform for ML/GenAI (reusable modules, drift detection); secure packaging & containerization.
  • Experience deploying and operating compute for ML (EKS/ECS/Lambda), and secure data access patterns (Amazon Simple Storage Service (S3)/Virtual Private Cloud (VPC)/Identity and Access Management (IAM)/Key Management Service (KMS), private endpoints)
  • Experience implementing MLflow tracking, model registry & governed promotion, packaging & deployment to multi-target runtimes.
  • Experience operating real-time + batch/streaming inference workloads, ML observability, layered testing (unit/integration), workflow orchestration, and cost optimization.
  • Experience designing and implementing IAM least-privilege, secrets/key management for CI/CD pipelines; privacy and compliance awareness.

Preferred Qualifications:

  • Advanced GitLab CI (dynamic child pipelines, components, cross-project triggers, security scans, compliance gates).
  • Advanced Terraform (policy-as-code, gated plan/apply, environment promotion).
  • Advanced real-time serving (multi-tenant routing, dynamic model loading) and SLO-driven rollback/automation.
  • Databricks governance (Unity Catalog, lineage) and feature platform approval/reuse workflows.

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