- Work model
- Hybrid
- Experience
- 4+ years
- Employment
- Full Time
- Compensation
- Not disclosed
- Technology signal
- 14 tags
Technology context
14Parsed from the vacancy text; ordered by relevance to this role.
Full listing
Role description
ABOUT THE ROLE
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
REQUIREMENTS
- 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