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Razer

Razer Inc. is a global consumer electronics and technology company specializing in high-performance hardware, software, and digital services designed specifically for gamers and content creators. Founded in 2005 by Min-Liang Tan and Robert Krakoff, the company is dual-headquartered in Irvine, California, and Queenstown, Singapore.

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

Job Responsibilities :

This role will focus on designing and developing advanced computer vision solutions forinteractive 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 withdataengineers, 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,actionrecognition, segmentation,image classificationandvideo understanding.

  • Design andcontribute toend-to-endcomputer vision systems to meetfunctional, performance, and scalability requirements.

  • Collaboratewith 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.

Pre-Requisites :

Qualifications

  • Proven experience in developing and implementing computer vision algorithms and modelsinreal-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 visionormultimodal AI(academic or industry).

Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.

Are you game?

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