Model Optimization Engineer
Description For Model Optimization Engineer
World Labs is at the forefront of artificial intelligence innovation, focusing on developing Large World Models that extend AI capabilities beyond traditional language and 2D visual processing into complex 3D environments. As a Model Optimization Engineer, you'll play a crucial role in enhancing the performance of large-scale foundation models and collaborating with Research Scientists to optimize systems utilizing thousands of GPUs for AI model training.
The position requires expertise in PyTorch, CUDA, and distributed systems, where you'll be responsible for implementing efficient solutions for data processing, training, and deployment. Your work will involve identifying optimization techniques, profiling efficiency bottlenecks, and developing high-performance code using CUDA, Triton, C++, and PyTorch. You'll also be instrumental in building tools for dataset visualization and evaluation, while implementing prototypes for multimodal generative AI features.
The ideal candidate is a fearless innovator who thrives on challenges and isn't afraid to tackle seemingly impossible problems. We're seeking resilient builders who can persevere through the complexities of groundbreaking research while maintaining a mission-driven mindset focused on creating the best spatially intelligent AI systems. Your collaborative spirit will be essential as we work together to harness collective intelligence and push the boundaries of AI technology.
At World Labs, you'll be joining a team of the brightest minds from around the globe, bringing diverse perspectives to cutting-edge work. This is an opportunity to work on technology that will fundamentally reshape how machines perceive and interact with the world. If you're passionate about advancing AI technology and want to be part of a team that's making history, World Labs offers the perfect launchpad for your career.
Responsibilities For Model Optimization Engineer
- Enhance performance of large-scale foundation models
- Collaborate with Research Scientists to optimize systems using thousands of GPUs
- Identify optimization techniques and profile efficiency bottlenecks
- Develop high-performance code in CUDA, Triton, C++, and PyTorch
- Build tools to visualize and evaluate datasets
- Implement prototypes for multimodal generative AI features
Requirements For Model Optimization Engineer
- Proficiency in Python and PyTorch with practical experience across the development pipeline
- Experience optimizing and deploying inference workloads
- Skilled in profiling CPU and GPU code using tools such as Nvidia Nsight
- Experience writing and improving parallel and distributed PyTorch code
- Familiarity with high-performance parallel C++ in machine learning contexts
- Proficiency in Triton, CUDA, and writing custom PyTorch kernels
- Understanding of deep learning architectures
- Experience building prototype applications using tools like Gradio and Docker
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