Job details

Model Optimization Engineer

At World Labs, our mission is to revolutionize artificial intelligence by developing Large World Models, taking AI beyond language and 2D visuals into the realm of complex 3D environments, both virtual and real. We're the team that's envisioning a future where AI doesn't just process information but truly understands and interacts with the world around us.

We're looking for the overachievers, the visionaries, and the relentless innovators who aren't satisfied with the status quo. You know that person who's always dreaming up the next big breakthrough? That's us. And we want you to be part of it.

As a Model Optimization Engineer at World Labs, you'll enhance the performance of large-scale foundation models, collaborating with Research Scientists to optimize systems using thousands of GPUs for training AI models. This role involves tackling challenges in PyTorch, CUDA, and distributed systems, ensuring efficient implementations for data processing, training, and deployment. You'll identify optimization techniques, profile efficiency bottlenecks, and develop high-performance code in CUDA, Triton, C++, and PyTorch. Additionally, you'll build tools to visualize and evaluate datasets and implement prototypes for multimodal generative AI features.

Key Qualifications:

Proficiency in Python and PyTorch with practical experience across the development pipeline: data processing, preparation, training, and inference.
Experience optimizing and deploying inference workloads with a focus on throughput and latency.
Skilled in profiling CPU and GPU code using tools such as Nvidia Nsight.
Experience writing and improving parallel and distributed PyTorch code using techniques like DDP, FSDP, or Tensor Parallel.
Familiarity with high-performance parallel C++ in machine learning contexts (e.g., for data loading and processing).
Proficiency in Triton, CUDA, and writing custom PyTorch kernels, including tensor core utilization and memory optimization.
Understanding of deep learning architectures such as Transformers, Diffusion Models, and GANs.
Experience building prototype applications using tools like Gradio and Docker.

A strong foundation in distributed computing and experience with large-scale AI training systems, preferred.
Familiarity with multimodal generative models and emerging AI paradigms, preferred.
Hands-on experience with dataset curation and visualization tools, preferred.
Passion for collaborating with research teams to translate cutting-edge concepts into real-world solutions, preferred.

Who You Are:

Fearless Innovator: We need people who thrive on challenges and aren't afraid to tackle the impossible.
Resilient Builder: Impacting Large World Models isn't a sprint; it's a marathon with hurdles. We're looking for builders who can weather the storms of groundbreaking research and come out stronger.
Mission-Driven Mindset: Everything we do is in service of creating the best spatially intelligent AI systems, and using them to empower people.
Collaborative Spirit: We're building something bigger than any one person. We need team players who can harness the power of collective intelligence.

We're hiring the brightest minds from around the globe to bring diverse perspectives to our cutting-edge work. If you're ready to work on technology that will reshape how machines perceive and interact with the world - then World Labs is your launchpad.

Join us, and let's make history together.

Average salary estimate

$135000 / YEARLY (est.)

min

max

$120000K

$150000K

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What You Should Know About Model Optimization Engineer, World Labs

At World Labs, our mission is to revolutionize artificial intelligence by developing Large World Models that extend AI's capabilities beyond language and 2D visuals into intricate 3D environments. We're on the lookout for a Model Optimization Engineer who not only understands the complexities but also excels in overcoming them. This role is all about enhancing the performance of large-scale foundation models. Picture yourself working closely with our innovative Research Scientists, optimizing systems that deploy thousands of GPUs to train AI models. Your day-to-day will involve tackling challenges in PyTorch and CUDA while ensuring that our implementations are as efficient as possible for data processing, training, and deployment. You'll have the chance to identify optimization techniques and profile efficiency bottlenecks while writing high-performance code in CUDA and PyTorch. Plus, you’ll play a pivotal role in building tools for visualizing datasets and prototyping features that fuel multimodal generative AI. If you're proficient in Python, PyTorch, and have a solid understanding of deep learning architectures, this could be your dream position. We're looking for fearless innovators who have a passion for collaboration and a mission-driven mindset. If you're ready to tackle groundbreaking research that pushes the boundaries of AI technology, then we want you on our team. Apply to become a Model Optimization Engineer at World Labs and help shape the future of how machines perceive and interact with our world!

Frequently Asked Questions (FAQs) for Model Optimization Engineer Role at World Labs

What are the main responsibilities of a Model Optimization Engineer at World Labs?

As a Model Optimization Engineer at World Labs, your primary responsibilities will include enhancing the performance of large-scale foundation models, collaborating with Research Scientists, optimizing systems for training AI models using thousands of GPUs, and implementing efficient data processing workflows. You will also identify optimization techniques, profile efficiency bottlenecks, and develop high-performance code in CUDA and PyTorch to support various AI initiatives.