Chief AI Delivery Officer

3 days ago

Mangalore, Karnataka, India beBeeMachineLearningOperations Full time ₹ 20,00,000 - ₹ 25,00,000
Senior MLOps Engineer Job Description

We are seeking a highly skilled Senior Machine Learning Operations (MLOps) Engineer to join our team. As an MLOps Engineer, you will play a critical role in ensuring the smooth operation of our machine learning models.

  • You will be responsible for owning the productionization process, from experimentation to governed releases.
  • Ensure that services are resilient with clear Service Level Objectives (SLOs), runbooks, and fast, safe rollbacks.

This involves building automation-first delivery pipelines using GitLab CI and Terraform-based Infrastructure as Code (IaC) to ensure reproducible builds, layered tests, and environment promotion.

Key Responsibilities:
  • Engineer scalable serving systems, including batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving, with features such as probes, autoscaling, and canary/blue-green deployments.
  • Instrument end-to-end observability (data, model, system) to 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.
Required Skills and Qualifications:
  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience in MLOps; or High School Diploma/General Education Degree and 6+ years of relevant experience 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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