About the Role

We are looking for an MLOps Developer to own the model lifecycle, deployment pipelines, and operational health of this AI system. You will bridge the gap between model development and production, ensuring models are reliably trained, versioned, deployed, and monitored across diverse hardware settings.

Key Responsibilities
Optimize and deploy PyTorch models (detection + video classification) to TensorRT and ONNX for real-time GPU inference across both server and edge hardware.
Build and maintain reproducible model training and evaluation pipelines with experiment tracking and dataset versioning
Design CI/CD workflows for model validation, packaging, and rollout to remotely deployed devices.
Monitor production inference pipelines — GPU utilization, latency, frame throughput, and model performance drift
Manage cloud storage (AWS S3) for model artifacts, video clips, and deployment assets
Containerize services (Docker) and investigate Kubernetes-based orchestration for multi-site deployments for edge hardware environments




Collaborate with ML and CV engineers to operationalize recent model versions and document deployment runbooks

Requirements
2–4 years of MLOps or ML engineering experience in production.
Robust Python; hands-on with PyTorch, ONNX, and TensorRT
Experience with CI/CD tools, Docker, and Linux/bash environments
Familiarity with experiment tracking (MLflow, ClearML, W&B;, or similar)
AWS or Azure cloud experience with exposure to ML-specific services such as:
AWS: SageMaker (training jobs, model registry, endpoints), ECR, S3, Lambda, CloudWatch
Azure: Azure Machine Learning (pipelines, model registry, compute clusters), Azure Container Registry, Blob Storage, Azure Monitor

Nice to Have
NVIDIA Jetson edge device deployment experience (JetPack/aarch64)
Real-time video processing (OpenCV, GStreamer, RTSP)
Dataset versioning tools (DVC or similar)
WebRTC or WebSocket-based streaming experience
Exposure to Docker / Kubernetes for model serving at scale

📌 Mlops Engineer Indore
🏢 Ignatiuz
📍 Indore