Senior AI Engineering Lead

2 days ago

Cochin, Kerala, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Key Responsibilities:

  • Develop and maintain resilient ML services with clear Service Level Objectives (SLOs), runbooks, and fast, safe rollbacks.
  • Implement automation-first delivery pipelines using GitLab CI and Terraform-based Infrastructure as Code (IaC).
  • Design scalable serving solutions for batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.
  • Establish end-to-end observability (data, model, system) to detect drift/regressions and lead incident investigations and post-mortem analysis.
  • Collaborate across teams to translate requirements into designs, Architecture Decision Records (ADRs), and change plans while balancing security, privacy, cost, and performance tradeoffs.
  • Continuously reduce toil through automation and optimize model/GPU/LLM cost to 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 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.

Benefits:

  • Collaborative environment
  • Opportunities for professional growth and development

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