Chief AI/Computer Vision Engineer

Join us as a Chief AI/Computer Vision Engineer leading the development of cutting-edge AI technologies focused on analyzing visual data and enhancing personalized client recommendations.You will oversee the deployment of computer vision, semantic image interpretation, and behavioral AI into scalable, intelligent platforms. Take this opportunity to drive innovative AI solutions that improve client interactions and deliver significant impact. ResponsibilitiesDevelop and refine CNN and transformer-based vision algorithms for image analysis and scoringCreate and implement specialized transformer frameworks for product innovationConstruct reliable pipelines to process large-scale image datasets and generate organized metadataIncorporate visual intelligence into functionalities such as search, ranking, and personalizationDeploy transformer-driven models to deliver customized product suggestionsLead experimentation including A/B testing to enhance recommendation performance and conversion metricsOversee and document the entire ML model lifecycle from design to deploymentCoordinate with multidisciplinary teams to direct technical projects from ideation to completionMaintain compliance with best practices in data management, model validation, explainability, and system monitoring RequirementsExtensive software engineering background with more than 7 years in AI/ML specialtiesExpertise in computer vision techniques including CNNs, vision transformers, facial recognition, object detection, image classification, and embeddingsStrong experience in recommendation algorithms, collaborative filtering, deep learning personalization, and transformer-based methodsProficiency in Python alongside ML frameworks like PyTorch and TensorFlowExperience in scaling machine learning solutions using Docker, AWS, GCP, or similar servicesProven leadership in managing cross-functional technical initiatives from start to finishThorough knowledge of ML lifecycle best practices covering data handling, model evaluation, explainability, and observabilityMaster’s degree in Computer Science or related field with emphasis on mathematics or physicsEnglish proficiency at B2 level or higher Nice to haveHands-on experience with diffusion modelsFamiliarity with graph neural networks (GNNs)Understanding of reinforcement learning principles We offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn