Senior AI Delivery Specialist

2 days ago

Tirupati, Andhra Pradesh, India beBeeMachineLearningEngineer Full time ₹ 1,20,00,000 - ₹ 2,00,00,000

Job Overview

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  • As a Senior MLOps Engineer, you will be responsible for driving the productionization of models, ensuring resilient services with clear service level objectives (SLOs), runbooks, and fast, safe rollbacks.
  • You will build automation-first delivery pipelines using GitLab CI and Terraform-based Infrastructure as Code (IaC) to streamline our ML operations.
  • With your expertise in scalable serving architectures, you will engineer batch and real-time inference on Amazon EKS/ECS/Lambda and Databricks Model Serving with 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 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/LLM cost, and evolve templates/playbooks for repeatable delivery.
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Key Qualifications

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  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience in model operations, machine learning engineering, or a related field.
  • 3+ years operating ML systems in production.
  • 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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