GPU Computer Vision Engineer

We're seeking passionate, driven, and self-motivated individuals to join our team. If you're eager to grow in a dynamic environment and be part of a company that’s at the forefront of AI innovation, this is your chance to hit the ground running.

VIDIZMO is a USA-based technology company headquartered in Tysons, Virginia, and a

Microsoft Solutions Partner

in

Data & AI ,

Infrastructure , and

Digital & App Innovation . Offering a

AI-Powered Intelligence Hub , we empower

Fortune 500 companies ,

large enterprises , governments, and the

public sector

to securely manage, analyze, and govern their data with complete control and compliance.

Our

Multimodal AI Data Intelligence Platform

leverages

Large Language Models (LLMs)

and

RAG (Retrieval-Augmented Generation)

to deliver powerful capabilities such as

auto-tagging ,

redaction ,

content summarization ,

OCR ,

translation ,

subtitle creation ,

object detection and tracking ,

content search ,

sentiment and emotion analysis ,

topic extraction ,

document classification , and

facial attribute detection.

About the Role

We are seeking an experienced Computer Vision & Video Analytics Engineer with deep expertise in TensorRT optimization and GPU-accelerated inference . In this role, you will build and optimize real-time intelligent video analytics (IVA) systems by bridging cutting-edge ML models with high-performance production pipelines.

You will architect low-latency, GPU-accelerated video solutions using TensorRT, CUDA, NVIDIA DeepStream, and GStreamer , ensuring scalable, production-grade deployment across edge and cloud environments.

Responsibilities

• Architect and optimize real-time video analytics pipelines using NVIDIA DeepStream and GStreamer.

• Lead TensorRT-based model optimization, including precision tuning (FP16/INT8), engine building, and performance benchmarking.

• Maximize GPU throughput and minimize latency using CUDA kernels, memory optimization, and parallelization techniques.

• Integrate computer vision models (detection, segmentation, tracking, classification) into high-performance production systems.

• Develop clean and efficient C/C++ and Python code in Linux-based environments.

• Troubleshoot, debug, and optimize GPU-accelerated inference pipelines.

• Collaborate with ML, hardware, and backend engineering teams to refine and deploy end-to-end AI systems.

• Participate in system design, code reviews, performance tuning, and optimization cycles.

Requirements

• Professional experience in computer vision, GPU acceleration, or high-performance computing.

• Strong proficiency in C/C++ and Python.

• Hands-on experience with:

TensorRT (model conversion, calibration, engine building, profiling)

• CUDA programming

• NVIDIA DeepStream SDK

• GStreamer pipelines

• Strong background in CV frameworks: PyTorch, TensorFlow, ONNX, OpenCV.

• Understanding of core CV tasks: detection, segmentation, classification, tracking, and model optimization.

• Familiarity with Kafka, MQTT, or microservice-based architectures.

• Excellent debugging and performance engineering skills in GPU-accelerated environments.

• Bachelor's or Master’s in Computer Science, Electrical Engineering, or related fields.

Preferred Qualifications

• Experience with Docker, containerization, and Kubernetes.

• Familiarity with NVIDIA Jetson, Orin, or edge AI devices.

• Experience building custom GStreamer plugins or low-level CUDA kernels.

• Knowledge of distributed inference or multi-GPU optimization.

Essential Skills:

The ideal candidate demonstrates strong business acumen, can translate objectives into impactful solutions, and is proficient in leveraging AI tools—including mandatory use of platforms like ChatGPT—to enhance efficiency. An ownership mindset and the ability to drive outcomes with minimal task-level direction are essential.

Benefits: Health Insurance (OPD/IPD), Separate Maternity Cover, Leave encashment, Car Support Program, Referral Bonus, EOBI, Bi-Annual Increment. Provident Fund, Career Growth, Bonus (benefits vary based on location)

Multiple Locations:

Pakistan, India, UAE, Australia, Canada & USA