AI Infrastructure Lead

4 days ago

Nagpur, Maharashtra, India beBeeMLOps Full time ₹ 1,77,50,000 - ₹ 2,53,85,000

About this role:

Seeking a seasoned MLOps Engineer to lead the development and deployment of AI infrastructure. This position involves partnering with cross-functional teams to deliver high-quality ML pipelines, model serving, and real-time monitoring.

Key responsibilities include:

MLOps Pipelines

Design and implement scalable machine learning pipelines for LLMs, CV, and multimodal models.

Model Serving & CI/CD

Lead efforts in model serving, versioning, automated CI/CD, and real-time monitoring of AI workflows.

Inference-as-a-Service

Build and optimize GPU-backed serving infrastructure targeting p99 latency < 100 ms, 99.9% uptime, and > 80% GPU utilization.

Governance & Drift Detection

Drive initiatives on model governance, automated drift detection (≤10% false positives), and data-management best practices.

Vector Search & Agent Orchestration

Integrate vector databases for low-latency semantic retrieval, and build agentic workflows using LangChain or similar frameworks.

Enterprise Multi-Tenancy

Architect RBAC-driven, isolated ML services to securely serve 100–500+ organizations.

Observability & Logging

Design Prometheus/Grafana dashboards, ELK/Fluentd logging pipelines, and alerting for all ML workloads.

CI/CD for Inference APIs

Maintain CI/CD pipelines for Python (FastAPI) and TypeScript (NestJS) inference services.

Metrics & Cost Optimization

Define and track SLAs/SLOs, optimize cloud spend by ≥ 20% year-over-year, and ensure GPU clusters operate at > 80% utilization.

Cross-Functional Leadership

Partner with AI researchers, product managers, and legal to align MLOps standards with compliance and roadmap goals.

Mentorship & Community

Mentor junior engineers, run quarterly brown-bags, own onboarding docs (upskill 5+ engineers/quarter), and publish ≥ 1 open-source contribution or talk annually.

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