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Senior Computer Vision Engineer

SoftServeRomania
Work model
Hybrid
Experience
4+ years
Employment
Full Time
Compensation
Not disclosed
Technology signal
14 tags

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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