Lead AI/Computer Vision Engineer

Become a Lead AI/Computer Vision Engineer driving the creation of advanced AI solutions that analyze visual content and personalize product recommendations.

You will spearhead the integration of computer vision, semantic image understanding, and behavioral AI into scalable intelligent systems. Join us to shape innovative AI technologies that elevate client experiences and deliver impactful results.

Responsibilities

• Develop and enhance CNN and transformer-based vision models for image evaluation and scoring
• Design and implement custom transformer architectures to support product development
• Build robust pipelines to handle high volumes of image data and produce structured metadata
• Integrate visual intelligence into applications like search, ranking, and personalization
• Deploy transformer-based models for tailored product recommendations
• Lead experimentation processes including A/B testing to optimize recommendation quality and conversion rates
• Manage and document the complete ML model lifecycle from development to deployment
• Collaborate with cross-functional teams to lead technical initiatives from concept through execution
• Ensure adherence to best practices in data handling, model assessment, explainability, and monitoring

Requirements

• Extensive software engineering experience with over 5 years focused on AI/ML roles
• In-depth expertise in computer vision methods including CNNs, vision transformers, facial recognition, object detection, image classification, and embeddings
• Strong background in recommendation systems, collaborative filtering, deep learning personalization, and transformer-based recommendation techniques
• Proficiency in Python and ML frameworks such as PyTorch and TensorFlow
• Experience deploying machine learning models at scale using Docker, AWS, GCP, or equivalent platforms
• Demonstrated leadership in managing cross-functional technical projects from inception to delivery
• Comprehensive understanding of ML lifecycle best practices including data management, model evaluation, explainability, and observability
• Master’s degree in Computer Science or a related discipline, preferably with a math or physics emphasis
• English communication skills at B2 level or above

Nice to have

• Practical experience with diffusion models
• Knowledge of graph neural networks (GNNs)
• Understanding of reinforcement learning concepts

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