New opportunities in Latin America!
🟢 Dev.Pro is a US-based software development company helping tech companies build their products and grow their business. We’re remote-first, and we work with independent contractors in over 55 countries, so you’d be collaborating in a multicultural environment on some really interesting projects.
We invite a skilled AI Engineer to join our team in building GPU-accelerated video analytics for real-time safety monitoring across large fleets and industrial environments. In this role, you’ll help design and optimize pipelines that detect and track actionable safety events in high-volume video streams. You’ll work on real-world systems that make an impact, collaborating with engineering and product teams to deliver reliable, high-performance solutions.
🟩 What's in it for you:
Collaborate with top engineers on an innovative, technically challenging computer vision project
Build impactful systems that enhance safety across large fleets and industrial operations
Gain hands-on experience with GPU-accelerated video analytics, temporal tracking, and real-time safety monitoring
✅ Is that you?
Desirable:
🧩Key responsibilities and your contribution
In this role, you’ll develop and maintain robust backend solutions that process video data and deliver actionable insights using pre-trained computer vision models.
Develop and optimize GPU-accelerated video inference pipelines for real-time processing
Implement, evaluate, and improve object detection models (YOLO or similar)
Build temporal smoothing and tracking logic for safety event detection
Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools
Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services
Add metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs
Contribute to dataset curation, labeling, and model evaluation; fine-tuning/training as needed
Support containerized deployments (Docker) and assist with monitoring and scaling production workload
Our next steps:
✅ Submit a CV in English — ✅ Intro call with a Recruiter — ✅ Interview — ✅ Signing the Contract
Interested? Find out more:
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Summary
Build GPU-accelerated video analytics pipelines for real-time safety monitoring across fleets and industrial environments, optimizing YOLO-based detection, tracking, and inference with TensorRT, CUDA, and ONNX. Requires 7+ years software engineering and 3+ years shipping computer vision to production with strong Python.
Responsibilities
Develop and optimize GPU-accelerated video inference pipelines; Implement and improve YOLO object detection models; Build temporal smoothing and tracking logic; Optimize with TensorRT, ONNX, CUDA; Maintain Azure integrations, telemetry and Docker deployments
Qualifications
Strong Python proficiency; Experience with OpenCV, PyTorch, async I/O frameworks, and API integrations; Hands-on YOLO/Ultralytics; Experience detecting, labeling, and tracking objects in video; GPU inference optimization
Experience requirements
7+ years of software engineering experience with strong backend skills; 3+ years shipping computer vision solutions to production; Upper-Intermediate+ English level
Interview process
Submit a CV in English; Intro call with a Recruiter; Interview; Signing the Contract
How to apply
Submit a CV in English