This role will focus on designing and developing advanced computer vision solutions for interactive systems. The ideal candidate will have strong expertise in core computer vision techniques such as object detection, tracking, segmentation, image classification, and video analysis, along with experience extending these capabilities for richer semantic understanding. This role involves working closely with data engineers, game developers, and software engineers to build scalable, production-ready vision systems that enable robust perception, automated analysis, and fast iteration in real-world environments.

Essential Duties and Responsibilities

• Develop and implement computer vision algorithms for tasks such as object detection, tracking, action recognition, segmentation, image classification and video understanding.

• Design and contribute to end-to-end computer vision systems to meet functional, performance, and scalability requirements.

• Collaborate with data engineering team to design annotation schemas, labeling taxonomies, and data validation strategies for large-scale image, video, and multimodal datasets supporting computer vision and multimodal model training.

• Train, fine-tune, and optimize computer vision models using machine learning frameworks and deep learning libraries.

• Evaluate the performance of computer vision models using appropriate metrics and benchmarks.

• Optimize models for real-time inference, edge deployment, or large-scale serving, considering latency, memory, and throughput constraints.

• Work closely with software engineering teams to support the integration and deployment of computer vision and multimodal models into production systems via APIs and messaging frameworks.

• Conduct testing and validation to ensure the functionality, reliability, and accuracy of computer vision systems.

• Document design specifications, technical requirements, and implementation details for computer vision solutions.

• Stay updated on emerging technologies, trends, and advancements in computer vision through research and experimentation.

• Consider ethical, legal, and regulatory implications in the development and deployment of computer vision systems.

Qualifications

• Proven experience in developing and implementing computer vision algorithms and models in real-world applications.

• Proficiency in programming languages such as Python or C++.

• Strong understanding of image and video processing techniques and methodologies.

• Hands-on experience with computer vision libraries (e.g., OpenCV) and deep learning frameworks such as PyTorch and TensorFlow for developing and training vision models.

• Experience defining data requirements and working with annotated datasets for computer vision model training.

• Ability to evaluate and optimize model performance using task-specific metrics and benchmarks.

• Strong analytical and problem-solving skills.

• Excellent written and verbal communication skills across technical and non-technical teams.

Preferred

• Experience with Vision-Language Models (VLMs), multimodal learning, or generative AI for vision tasks.

• Experience with messaging and communication technologies such as RabbitMQ, gRPC, REST APIs for service integration.

• Exposure to distributed training, large-scale experiments, or multi-GPU systems.

• Experience with model optimization and deployment (e.g., ONNX, TensorRT, edge or real-time inference).

Education & Experience

• Master’s or PhD in a relevant field (Computer Science, AI, Machine Learning, etc.).

• 2+ years of applied experience in computer vision or multimodal AI (academic or industry).