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# Platform Engineer III

- **Company:** HCL Technologies
- **Location:** Tampa, FL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Cloud Computing, Nvidia CUDA, Computer Programming, Data Transformation, DevOps, Python (Programming Language), Machine Learning, Object Detection, Systems Development Life Cycle, Software Deployment, Enterprise Software Applications, Deep Learning, Real-time Inference, Low Latency, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, TensorRT, Video Analysis, NVIDIA Jetson, Intelligent Document Processing, Pose Estimation
- **Published:** November 3, 2026
- **Apply:** https://www.careerbuilder.com/job-details/platform-engineer-iii-tampa-fl--a51efa60-31a2-4e49-9ed4-765a21408d14

## About the Role

Automation, Retail, Logistics, Deep Learning, Manufacturing, Artificial Intelligence (AI), Computer Vision, Cloud Computing, Scalable System Development, Training Data Sets, Strong programming experience in Python, Understanding of image processing, video analytics, and deep learning fundamentals.

Other Requirements

Good to have

Familiarity with Azure, AWS, or GCP environments.

Experience with NVIDIA Jetson platforms.

Knowledge of CUDA, TensorRT, DeepStream SDK.

Exposure to real-time edge AI deployments.

## Description

VisionX is HCLTechs Physical AI platform focused on delivering intelligent computer vision solutions for manufacturing, logistics, retail, smart spaces, and industrial automation. We are looking for a passionate Senior Computer Vision Developer to design, develop, and deploy scalable vision AI solutions leveraging deep learning, edge AI, and cloud technologies., Design, develop, and optimize Computer Vision solutions for: Object Detection, Image Classification, Semantic & Instance Segmentation, OCR & Document AI, Pose Estimation, Video Analytics, Anomaly Detection.

Train, fine-tune, and evaluate deep learning models using large-scale image and video datasets. Develop AI pipelines from data collection, preprocessing, model training, inference, and deployment.

Optimize AI models using ONNX, TensorRT, OpenVINO, and CUDA for real-time inference.

Improve model accuracy, latency, throughput, and resource utilization.

Integrate Computer Vision models with enterprise applications and IoT platforms.

Collaborate with Full Stack, DevOps, and Edge AI teams for production deployments.