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Текст:
TL;DR
Senior Data Scientist (Computer Vision) (Computer Vision/Multimodal AI): Designing and developing production-ready computer vision systems for interactive gaming systems with an accent on object detection, tracking, segmentation, video understanding, and model optimization. Focus on building scalable perception pipelines, optimizing real-time and edge inference, and integrating multimodal models into production through APIs and messaging frameworks.
Location: Singapore office; occasional travel of up to one trip per year for conferences, research collaborations, or business meetings.
Company
Razer develops gamer-focused products and interactive systems as a global gaming company.
What you will do
- Develop computer vision algorithms for object detection, tracking, action recognition, segmentation, image classification, and video understanding.
- Design end-to-end vision systems that meet functional, performance, and scalability requirements.
- Define annotation schemas, labeling taxonomies, data requirements, and validation strategies for large-scale image, video, and multimodal datasets.
- Train, fine-tune, evaluate, and optimize computer vision and multimodal models.
- Optimize models for real-time inference, edge deployment, and large-scale serving under latency, memory, and throughput constraints.
- Integrate and deploy models into production systems with software engineers through APIs and messaging frameworks.
Requirements
- Proven experience developing computer vision algorithms and models for real-world applications.
- Proficiency in Python or C++ and strong knowledge of image and video processing.
- Hands-on experience with OpenCV, PyTorch, and TensorFlow.
- Experience working with annotated datasets and evaluating model performance with task-specific metrics and benchmarks.
- Master’s or PhD in Computer Science, AI, Machine Learning, or a related field, plus 2+ years of applied computer vision or multimodal AI experience.
- Strong analytical, problem-solving, written communication, and verbal communication skills.
Nice to have
- Experience with Vision-Language Models, multimodal learning, or generative AI for vision tasks.
- Experience with RabbitMQ, gRPC, or REST APIs.
- Exposure to distributed training, large-scale experiments, or multi-GPU systems.
- Experience with ONNX, TensorRT, edge deployment, or real-time inference.
Culture & Benefits
- Work with a global team across five continents.
- Collaborate across data engineering, game development, and software engineering teams.
- Contribute to an inclusive and respectful workplace.
- Receive reasonable workplace accommodations where needed.
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