🟢 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 operationsGain 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 productionStrong Python proficiencyExperience with OpenCV, PyTorch, async I/O frameworks, and API integrations Hands-on experience with YOLO/Ultralytics or similar object detection frameworksExperience detecting, labeling, and tracking objects in videoSolid knowledge of frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregationExperience with GPU inference optimization (batching, stride, TensorRT, CUDA, quantization, throughput tuning) Ability to communicate and collaborate effectively with engineering and product teamsUpper-Intermediate+ English levelDesirable:Experience with Azure Event Hub, Blob Storage, Application Insights, or similarFamiliarity with Docker, cloud deployments, and production monitoring systems Experience in temporal/sequence analysis for event detectionExperience 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 processingImplement, evaluate, and improve object detection models (YOLO or similar)Build temporal smoothing and tracking logic for safety event detectionOptimize model performance using TensorRT, ONNX, CUDA, and GPU profiling toolsBuild and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal servicesAdd metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobsCollaborate on dataset curation, labeling, model training, validation, and experiment trackingSupport containerized deployments (Docker) and assist with monitoring and scaling production workloadOur next steps:✅ Submit a CV in English — ✅ Intro call with a Recruiter — ✅ Internal interview — ✅ Client interview — ✅ OfferInterested. Find out more:📋How we work💻 LinkedIn Page📈 Our website 💻IG Page.