Lead Computer Vision Engineer

About the Role

In this role, you will define the technical vision for computer vision and generative AI systems, spanning image generation, multimodal intelligence, and 3D scene understanding, within SoftServe's AI and Data Science Center of Excellence, a team of 170+ experts. You'll shape CV strategy for world-leading clients, drive innovation from research to production, and lead teams to deliver visual AI solutions that create measurable impact at scale.

Responsibilities

• Define and drive technical vision for computer vision systems, spanning generative AI, multimodal intelligence, and 3D scene understanding, ensuring alignment with business objectives and CoE innovation goals
• Oversee the design and delivery of production-ready CV pipelines using PyTorch, ONNX, TensorRT, or Triton, establishing engineering standards and quality benchmarks across the team
• Lead cross-functional collaboration with Data Scientists, MLOps Engineers, ML Architects, and clients, translating complex requirements into scalable visual AI solutions
• Advance generative and multimodal AI capabilities by architecting models, including diffusion systems, transformers, and vision-language models, optimized for production environments
• Establish and continuously improve CV engineering processes, from model training pipelines to cloud infrastructure on AWS, GCP, or Azure, and MLOps best practices
• Mentor and guide Computer Vision Engineers, embedding expertise in classical CV, deep learning, and emerging visual AI domains across the team
• Contribute to thought leadership through technical publications, client engagements, and participation in industry events and research communities

Requirements

• Extensive Python and PyTorch expertise with a proven track record of delivering end-to-end CV systems in production
• Deep knowledge of classical CV techniques, including camera calibration, feature matching, homography estimation, and geometric scene understanding
• Advanced experience with generative AI and multimodal systems, including diffusion models, transformers, and vision-language models
• Proven expertise in model optimization and deployment using ONNX, TensorRT, or Triton across cloud platforms (AWS, GCP, or Azure)
• Demonstrated experience leading or mentoring Computer Vision Engineering teams, driving technical direction, and embedding best practices
• Strong stakeholder management skills, with the ability to shape CV strategy and communicate technical decisions to clients and executive audiences
• 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