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Computer Vision/AI engineer

middleremoteСанкт-Петербург, RUScore 69.8/1001w ago
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cloudpythonpytorch
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Description
OnTarget Labs is a leading international software product development company. We create next generation of world class product lines. The company is looking for a Computer Vision/AI engineer to join our innovative product team as a full-time member working REMOTELY . Lots of opportunities for professional growth and business trips abroad are offered. Join our friendly team of IT professionals now! Product description We are building AI-powered tennis video analysis from smartphone-recorded match footage. Role description We are looking to bring in a Computer Vision + AI Engineer to support machine learning and video analytics work across multiple models and product capabilities. The role would support our internal team across the full CV/ML pipeline, from dataset quality and model evaluation through production-oriented model improvement, custom tracking/interpretation logic, and selective edge/mobile deployment. The engineer will operate under Head of Engineering / CTO guidance but should be skilled enough to independently assess problems, recommend experiments, implement improvements, and communicate technical tradeoffs clearly. Key skillset / experience requirements: Strong practical computer vision experience, especially with real-world video Strong Python and PyTorch experience Experience with object detection, object tracking, classification, and/or keypoint-style models Ability to evaluate model outputs, diagnose failure modes, and recommend targeted improvements Strong understanding of dataset strategy, annotation quality, validation design, and metric interpretation Experience designing or improving custom tracking, smoothing, temporal decoding, or model interpretation layers Experience improving models toward production-level robustness across diverse real-world conditions Experience deploying and optimizing cloud-based video processing pipelines Experience with on-device edge/mobile inference, and skilled with deployment workflows, such as ONNX, Core ML,
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