Machine Learning Infrastructure Engineer

2 days ago


Kozhikode, Kerala, India beBeeMloper Full time ₹ 21,28,000 - ₹ 30,24,000
Senior MLOps Engineer Opportunity

Seeking a seasoned Senior MLOps Engineer to lead the design, implementation, and scaling of AI infrastructure.

  • Design and implement scalable ML pipelines for LLMs, CV, and multimodal models.
  • Lead model serving, versioning, automated CI/CD, and real-time monitoring of AI workflows.
  • Build and optimize GPU-backed serving infrastructure targeting p99 latency < 100 ms, 99.9% uptime, and > 80% GPU utilization.
  • Drive initiatives on model governance, automated drift detection (≤10% false positives), 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 100–500+ organizations.

Responsibilities Include:

  • Observability & Logging: Design Prometheus/Grafana dashboards, ELK/Fluentd logging pipelines, and alerting for all ML workloads.
  • Cross-Functional Leadership: Partner with AI researchers, product managers, and legal to align MLOps standards with compliance and roadmap goals.

Requirements:

  • 9–14 years in software engineering, including ≥ 4 years in MLOps or ML infrastructure.
  • Strong expertise in cloud platforms (AWS/GCP/Azure), Kubernetes, Docker, Terraform, Helm, Kubeflow, and MLflow.
  • Experience with inference frameworks (Triton, TensorFlow Serving, BentoML, TorchServe).
  • Familiarity with distributed training, workload schedulers, and GPU-cluster orchestration.
  • Proficiency in Python, TypeScript, and infrastructure-as-code (Terraform, Helm, etc.).

Plus These Critical Skills:

  • Vector DB integration (Qdrant, Pinecone).
  • Agent orchestration (LangChain, LlamaIndex).
  • Multi-tenant security and RBAC.
  • Observability stacks (Prometheus/Grafana, ELK).


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