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.

Responsibilities

• Develop and refine CNN and transformer-based vision algorithms for image analysis and scoring
• Create and implement specialized transformer frameworks for product innovation
• Construct reliable pipelines to process large-scale image datasets and generate organized metadata
• Incorporate visual intelligence into functionalities such as search, ranking, and personalization
• Deploy transformer-driven models to deliver customized product suggestions
• Lead experimentation including A/B testing to enhance recommendation performance and conversion metrics
• Oversee and document the entire ML model lifecycle from design to deployment
• Coordinate with multidisciplinary teams to direct technical projects from ideation to completion
• Maintain compliance with best practices in data management, model validation, explainability, and system monitoring

Requirements

• Extensive software engineering background with more than 7 years in AI/ML specialties
• Expertise in computer vision techniques including CNNs, vision transformers, facial recognition, object detection, image classification, and embeddings
• Strong experience in recommendation algorithms, collaborative filtering, deep learning personalization, and transformer-based methods
• Proficiency in Python alongside ML frameworks like PyTorch and TensorFlow
• Experience in scaling machine learning solutions using Docker, AWS, GCP, or similar services
• Proven leadership in managing cross-functional technical initiatives from start to finish
• Thorough knowledge of ML lifecycle best practices covering data handling, model evaluation, explainability, and observability
• Master’s degree in Computer Science or related field with emphasis on mathematics or physics
• English proficiency at B2 level or higher

Nice to have

• Hands-on experience with diffusion models
• Familiarity with graph neural networks (GNNs)
• Understanding of reinforcement learning principles

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn