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
