Description

Join Razer's global team to revolutionize gaming.

Job Responsibilities

Design and develop advanced computer vision solutions for interactive systems.

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.
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.
Work closely with software engineering teams to support the integration and deployment of computer vision and multimodal models into production systems.
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.
Consider ethical, legal, and regulatory implications in the development and deployment of computer vision systems.

Pre-Requisites

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.
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).

Travel Requirements

Occasional travel (up to 1 trip per year) for conferences, research collaborations, or business meetings.