Senior Machine Learning Operations Engineer

3 days ago

Salem, Tamil Nadu, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Overview

We are seeking a skilled professional to lead the development of our AI infrastructure. As a Senior MLOps Engineer, you will partner with researchers and product teams to turn prototypes into production services that meet strict performance requirements.

Main Responsibilities:

  • Design and implement scalable ML pipelines for large-scale models.
  • Lead efforts in model serving, versioning, automated CI/CD, and real-time monitoring of AI workflows.
  • Build and optimize GPU-backed serving infrastructure targeting low latency and high uptime.
  • Drive initiatives on model governance, automated drift detection, and data-management best practices.
  • Integrate vector databases for low-latency semantic retrieval and build agentic workflows using LangChain or similar frameworks.
  • Architect RBAC-driven, isolated ML services to securely serve multiple organizations.
  • Design dashboards, logging pipelines, and alerting for all ML workloads.
  • Maintain CI/CD pipelines for Python (FastAPI) and TypeScript (NestJS) inference services.

Key Qualifications:

  • 9-14 years of experience in software engineering, including 4+ years in MLOps or ML infrastructure.
  • Strong expertise in cloud platforms, Kubernetes, Docker, Terraform, Helm, Kubeflow, and MLflow.
  • Experience with inference frameworks and distributed training.
  • Familiarity with workload schedulers and GPU-cluster orchestration.
  • Proficiency in Python, TypeScript, and infrastructure-as-code.

Plus These Critical Skills:

  • Vector DB integration.
  • Agent orchestration.
  • Multi-tenant security and RBAC.
  • Observability stacks.
  • CI/CD for FastAPI/NestJS services.

Preferred:

  • Master's/PhD in CS/AI and certifications like AWS ML Specialty.
  • Prior experience at AI-focused startups or enterprises scaling ML for multiple orgs.
  • Understanding of low-latency streaming inference or agent-based LLM systems.

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