Senior Artificial Intelligence Operations Manager

2 days ago

Bharatpur, Rajasthan, India beBeeMachine Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Overview

We are seeking a highly skilled Senior Machine Learning Operations Engineer to lead our ML engineering efforts.

Key Responsibilities:
  • Productionize models from tracked experiments to governed releases, ensuring resilient services with clear service level objectives, runbooks, and fast, safe rollbacks.
  • Build automation-first delivery: reproducible builds, layered tests, and environment promotion via GitLab CI and Terraform-based infrastructure as code.
  • Engineer scalable serving: batch and real-time inference on Amazon Elastic Container Service for Kubernetes, 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, architectural decision records, and change plans; balance 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 machine learning systems in production (MLOps).
  • Experience with Python for machine learning engineering (packaging, typing, testing, performance)
  • Experience developing GitLab CI for machine learning/gen artificial intelligence (multi-stage pipelines, artifacts, evaluation/security gates) and Terraform for machine learning/gen artificial intelligence (reusable modules, drift detection); secure packaging & containerization.
  • Experience deploying and operating compute for machine learning (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, machine learning observability, layered testing (unit/integration), workflow orchestration, and cost optimization.
  • Experience designing and implementing identity and access management 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 service level objective-driven rollback/automation.
  • Databricks governance (Unity Catalog, lineage) and feature platform approval/reuse workflows.

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