Data Engineering Leader: AI Infrastructure

22 hours ago

Tirupati, Andhra Pradesh, India beBeeMloppsengineer Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Lead MLOps Engineer

About this role:

We are seeking a senior MLOps Engineer to lead the design, implementation, and scaling of our AI infrastructure. You'll partner with researchers, product teams, and DevOps to turn prototypes into production services that meet strict SLAs for latency, reliability, and cost efficiency.

Main Responsibilities:

  • Design and implement scalable machine learning pipelines (training, evaluation, deployment) for large language models, computer vision, and multimodal 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 p99 latency < 100 ms, 99.9% uptime, and > 80% GPU utilization.
  • Drive initiatives on model governance, automated drift detection ( 80% utilization.
  • Partner with AI researchers, product managers, and legal to align MLOps standards with compliance and roadmap goals.
  • Mentor junior engineers, run quarterly brown-bags, own onboarding docs (upskill 5+ engineers/quarter), and publish ≥ 1 open-source contribution or talk annually.

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.).
  • A proven track record building reliable, scalable ML systems in production.

Bonus Skills:

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

Nice to Have:

  • Master's/PhD in CS/AI and certifications such as AWS ML Specialty, Google Cloud Professional ML Engineer, or CNCF CKA/CKAD.
  • Prior experience at AI-focused startups or enterprises scaling ML for 100–500 orgs.
  • Understanding of low-latency streaming inference or agent-based LLM systems.
  • Excellent written and verbal communication, and a proven ability to drive consensus across functions.

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