ML Systems Specialist

2 weeks ago

Hyderabad, Telangana, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,20,00,000
Senior MLOps Engineer Job Summary

This is an exciting opportunity to work as a Senior MLOps Engineer. As a key member of the team, you will be responsible for productionizing models and ensuring resilient services with clear Service Level Objectives (SLOs), runbooks, and fast, safe rollbacks.

You will build automation-first delivery, reproducible builds, layered tests, and environment promotion via GitLab CI and Terraform-based Infrastructure as Code (IaC).

Additionally, you will engineer scalable serving, batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.

You will also instrument end-to-end observability (data, model, system); detect drift/regressions; lead incidents and post-mortems that drive durable fixes.

Finally, you will partner across teams to translate requirements into designs, Architecture Decision Records (ADRs), and change plans; balance security, privacy, cost, and performance tradeoffs.

Required Skills and Qualifications:
  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience as outlined in the essential duties; or High School Diploma/General Education Degree and 6+ years of relevant experience as outlined in the essential duties 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/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 (S3/VPC/IAM/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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