Job Description

🟢 We’re expanding our team and opening new remote opportunities! Review the role expectations, share your resume in English, and our team will follow up shortly.

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?

• 7+ years of software engineering experience with strong backend skills
• 3+ years of experience shipping computer vision solutions to production
• Strong Python proficiency
• Experience with OpenCV, PyTorch, async I/O frameworks, and API integrations
• Hands-on experience with YOLO/Ultralytics or similar object detection frameworks
• Experience detecting, labeling, and tracking objects in video
• Solid knowledge of frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregation
• Experience with GPU inference optimization (batching, stride, TensorRT, CUDA, quantization, throughput tuning)
• Ability to communicate and collaborate effectively with engineering and product teams
• Upper-Intermediate+ English level

Desirable:

• Experience with Azure Event Hub, Blob Storage, Application Insights, or similar
• Familiarity with Docker, cloud deployments, and production monitoring systems
• Experience in temporal/sequence analysis for event detection
• Experience with video analytics in safety, compliance, or industrial/transportation environments
  

🧩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
• Collaborate on dataset curation, labeling, model training, validation, and experiment tracking
• 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 — ✅ Internal interview — ✅ Client interview — ✅ Offer

Interested? Find out more:

📋How we work

💻 LinkedIn Page

📈 Our website

💻IG Page