AI ML Ops Engineer

About the role

We are seeking an AI/ML Ops Engineer to own the deployment, monitoring, and scaling of ML models and pipelines in production. You will build the infrastructure and automation that lets models move reliably from training to production and stay healthy once there.

What you'll do

• Deploy and scale ASR, NMT and TTS models on GPU servers using Docker, Kubernetes and Triton Inference Server
• Build and maintain CI/CD pipelines that take models from training to production
• Monitor services for latency, throughput, errors and GPU utilization, and help debug production issues
• Help optimize inference performance for real-time use cases such as live transcription and voice agents
• Help manage GPU capacity across cloud and on-prem environments

What you need

• 3–5 years in data science & ai
• MLOps
• Python
• AWS
• CI/CD
• Kubernetes
• Docker
• Any graduate

Good to have

• LLMs
• gRPC
• Prometheus
• Grafana
• Helm
• Terraform

What you get

• ₹9 L–₹10 L a year