Artificial Intelligence Deployment Expert

2 weeks ago

Anantapur, Andhra Pradesh, India beBeeMachineLearningOperations Full time ₹ 18,00,000 - ₹ 22,00,000
Job Title: Machine Learning Operations Specialist

The ideal candidate will be responsible for productionizing models, building automation-first delivery, and engineering scalable serving.

Key Responsibilities:

  • Own model productionization, ensuring resilient services with clear SLOs, runbooks, and fast, safe rollbacks.
  • Develop automation-first delivery: reproducible builds, layered tests, and environment promotion via GitLab CI and Terraform-based IaC.
  • Engineer scalable serving: batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.
  • Implement 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, ADRs, and change plans; balance security, privacy, cost, and performance tradeoffs.
  • 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 above; or High School Diploma/General Education Degree and 6+ years of relevant experience as outlined above 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.

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