Senior Computer Vision Engineer

In this role, you will push the boundaries of visual AI — designing and deploying computer vision systems that span image generation, multimodal intelligence, and 3D scene understanding. You will be a part of SoftServe's AI and Data Science Center of Excellence — a team of 170+ AI experts. Your solutions will ship to production for world-leading clients, making a direct and measurable difference across industries.

Responsibilities

• Design and implement advanced computer vision solutions for image and video generation, enhancement, and understanding tasks using PyTorch and state-of-the-art deep learning architectures
• Build, fine-tune, and deploy generative AI models — including diffusion models, transformers, and vision-language models — optimizing them for production environments using ONNX, TensorRT, or Triton
• Collaborate with Data Scientists, MLOps Engineers, ML Architects, and business stakeholders to translate complex requirements into scalable, production-ready CV pipelines
• Develop and maintain end-to-end model training and evaluation pipelines across research and production environments, leveraging cloud infrastructure on AWS, GCP, or Azure
• Apply classical computer vision techniques — including camera calibration, feature matching, and homography estimation — to address real-world geometric and scene understanding challenges
• Contribute to technical direction, share knowledge across the CoE, and help advance innovation in areas such as 3D computer vision, anomaly detection, edge AI, or model compression

• Strong Python and PyTorch skills with 4+ years of experience in computer vision and deep learning, including building end-to-end training pipelines
• Solid knowledge of classical computer vision techniques, including camera calibration, feature matching, homography estimation, and other geometric methods
• Advanced experience with multimodal and generative AI systems, including transformers, diffusion models, and vision-language models
• Proven expertise in model optimization and deployment for production using tools such as ONNX, TensorRT, or Triton
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and MLOps practices for scalable model lifecycle management
• Specialized knowledge in at least one advanced domain: 3D computer vision, anomaly detection, edge AI, or model compression
• Analytical background with a degree in Computer Science, Applied Mathematics, Physics, or a related field
• Upper-intermediate or higher proficiency in spoken and written English