Senior Machine Learning Engineer

1 day ago

Salem, Tamil Nadu, India beBeeMachineLearning Full time ₹ 16,38,400 - ₹ 23,45,678
Job Description:

Our ideal candidate will be responsible for driving the productionization of machine learning models. This includes owning the process from tracked experiments to governed releases, ensuring resilient services with clear service-level objectives (SLOs), runbooks, and fast, safe rollbacks.

Key Responsibilities:
  • 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 EKS/ECS/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, 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.
Minimum Qualifications:
  • 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.
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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