RoshAi
Website:
rosh.ai
Job details:
Role OverviewWe are seeking a hands-on Deployment Engineer to install, integrate, commission and support AI-powered computer vision and robotics products at customer sites. The role combines practical troubleshooting of cameras, lighting, sensors, industrial PCs, networks and robotic interfaces with software deployment, system validation and customer training. The engineer will work closely with AI, robotics, software and customer operations teams to ensure reliable production go-live.
Key Responsibilities
- Deploy and configure AI/computer vision products at customer facilities, including software, models, cameras, lighting, sensors and industrial PCs.
- Integrate vision solutions with robotic systems, PLCs, conveyors and other shop-floor equipment; coordinate with customer automation teams.
- Perform camera calibration, image acquisition setup, network configuration, system tuning and onsite functional testing.
- Validate object detection, inspection and tracking performance against agreed acceptance criteria; record test results and support site acceptance testing (SAT).
- Troubleshoot hardware, software, network, inference-performance and integration issues; escalate complex defects with reproducible logs and evidence.
- Support commissioning, production go-live, operator training, handover documentation, hypercare and incident resolution.
- Maintain installation checklists, configuration records, issue trackers and clear daily status updates for internal teams and customers.
Required Technical Skill Computer Vision & AI Deployment
- Working experience with OpenCV and deploying trained object detection, classification or segmentation models (e.g., YOLO).
- Python proficiency; familiarity with PyTorch or TensorFlow inference, image preprocessing and basic model-performance metrics.
Robotics & Industrial Integration
- Practical exposure to industrial robots or ROS/ROS2, robotic coordinate systems, hand–eye calibration or vision-guided robotics.
- Familiarity with PLC I/O, triggers, sensors, conveyors and industrial communication (e.g., TCP/IP, Modbus or OPC UA).
Hardware, Networking & Edge Systems- Hands-on camera setup (USB/GigE/industrial cameras), lens and lighting selection basics, calibration, industrial PCs and GPU/edge devices.
- Comfortable with Windows/Linux, IP addressing, Ethernet troubleshooting, remote access, log collection and software installation.
Testing, Support & Customer Delivery- Experience with commissioning, integration testing, defect isolation, root-cause analysis, SAT/UAT and production support.
- Strong onsite communication, documentation, customer coordination and willingness to travel for deployments.
Preferred / Good-to-Have Skills- NVIDIA Jetson, CUDA/TensorRT, Docker, Git, REST APIs or basic CI/CD knowledge.
- Multi-camera vision, 3D/depth cameras, sensor fusion, robotic motion planning or simulation exposure.
- Experience in manufacturing quality inspection, autonomous mobile robots or other industrial AI deployments.
Qualifications & Experience
- 2–3 years of relevant experience in AI/computer vision deployment, robotics integration, field application engineering or industrial automation.
- B.E./B.Tech or equivalent in Computer Science, Electronics, Electrical Engineering, Robotics, Mechatronics or a related discipline.
- Ability to independently handle routine site deployments and troubleshoot under guidance for complex system-level issues.
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