Company: Process Point Technologies

Location: Remote

Experience: 7+ years

Notice Period: Immediate joiners preferred

Shift: 2 PM – 11 PM IST (US overlap)

Role Overview

You will take computer vision models from development to real-time production on NVIDIA Jetson Orin edge devices,

supporting process control, safety, and quality use cases in industrial plant operations. On-device performance,

latency, and long-run stability matter as much as model accuracy.

Key Responsibilities

Edge Model Optimization & Deployment

- Convert and optimize PyTorch vision models (detection, segmentation, classification) to ONNX and TensorRT for Jetson

Orin

- Package inference workloads as Docker containers on JetPack/L4T (ARM64) with reproducible builds and deployments
- Work with data scientists to make models edge-ready (input sizing, architecture trade-offs, pre/post-processing)

Real-Time Video Pipelines
- Build and tune low-latency RTSP/GStreamer pipelines using hardware decode and zero-copy (NVMM) memory
- Develop DeepStream pipelines, including custom C++ parsers/plugins for non-standard model outputs
- Write performance-critical components in C++ and CUDA; use Python for integration and tooling
- Deliver model outputs to downstream systems (alerts, dashboards, PLC/control-system interfaces)

Validation, Profiling & Production Support
- Profile latency, throughput, GPU/CPU/memory utilization, and thermals (Nsight Systems, tegrastats)



and remove bottlenecks
- Engineer for 24/7 stability: stream reconnection, watchdogs, backpressure, frame-drop control, logging, and health monitoring
- Remotely support field testing and troubleshooting of deployed systems
- Document deployment procedures, configurations, and runbooks

Must Have

- Computer vision / ML engineering experience with models delivered to edge or embedded systems in production
- Hands-on NVIDIA Jetson Orin (AGX Orin / Orin NX / Orin Nano)
- Model optimization and deployment with TensorRT and ONNX
- Python and PyTorch
- Docker on ARM64 / JetPack / L4T
- Profiling and tuning for latency and long-running stability on constrained hardware
- Robust communication skills for working directly with client operations, automation, and IT/OT teams

Positive to Have

- NVIDIA DeepStream SDK, including custom plugins or output parsers
- CUDA and C++
- RTSP/GStreamer pipelines with IP cameras
- Industrial domain experience (mining, chemicals, manufacturing, energy) and OT integration (PLC, OPC UA, Modbus)
- Edge hardware and camera selection for remote sites
- Fleet management, remote updates, or monitoring for multiple edge devices
- Experience with enterprise change control and cybersecurity review processes

Key Skills: Computer Vision | NVIDIA Jetson | TensorRT | ONNX | DeepStream | CUDA | C++ | Python | PyTorch | GStreamer

Docker | Edge Deployment

📌 Computer Vision Engineer (India)
🏢 Process Point Technologies
📍 India