Model Operations Specialist

4 days ago

Gulbarga, Karnataka, India beBeeMLOps Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Our organization is looking for a highly skilled professional to join our team as a Model Operations Specialist. This role involves the ownership of model productionization, ensuring that services are resilient and meet specific Service Level Objectives (SLOs).

The ideal candidate will have experience operating machine learning systems in production, developing GitLab CI for ML/GenAI, and deploying and operating compute for ML. They should also be familiar with implementing MLflow tracking, model registry & governed promotion, packaging & deployment to multi-target runtimes.

Responsibilities:
  • Own the productionizing process, from tracked experiments to governed releases, ensuring that services are resilient and meet clear SLOs, runbooks, and fast, safe rollbacks.
  • Develop automation-first delivery: reproducible builds, layered tests, and environment promotion via GitLab CI and Terraform-based Infrastructure as Code (IaC).
  • Engineer scalable serving: batch and real-time inference on Amazon Elastic Container Service (ECS), AWS Lambda, and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.
  • Instrument end-to-end observability (data, model, system); detect drift/regressions; lead incidents and post-mortems that drive durable fixes.
  • Partner across teams to translate requirements into designs, Architecture Decision Records (ADRs), and change plans; balance security, privacy, cost, and performance tradeoffs.
  • Continuously reduce toil through automation, optimize model/GPU/Large Language Model (LLM) cost, and evolve templates/playbooks for repeatable delivery.
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 machine learning 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 (AWS ECS, AWS 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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