Hedra is a pioneering generative media company backed by top investors at Index, A16Z, and Abstract Ventures. We're building Hedra Studio, a multimodal creation platform capable of control, emotion, and creative intelligence.
At the core of Hedra Studio is our Character-3 foundation model, the first omnimodal model in production. Character-3 jointly reasons across image, text, and audio for more intelligent video generation — it’s the next evolution of AI-driven content creation.
Note: At Hedra, we’re a team of hard-working, passionate individuals seeking to fundamentally change content and build a generational company together. You should have start-up experience and be a self-starter that is driven to build impactful products that change the status quo. You must be willing to work in-person in either NYC or SF.
We are seeking a talented CUDA ML Engineer to optimize our machine learning models for high-performance computing on GPU hardware. The ideal candidate will have expertise in CUDA programming and a deep understanding of how to leverage GPU acceleration to maximize the efficiency of our 3DVAE and video diffusion models.
Optimize machine learning models, specifically 3DVAE and video diffusion models, for GPU performance using CUDA, ensuring efficient training and inference.
Develop and implement efficient algorithms and data structures for GPU computation, addressing performance bottlenecks in video generation tasks.
Work closely with the research and engineering teams to understand model requirements and performance bottlenecks, facilitating collaboration.
Stay current with the latest advancements in GPU technology and machine learning optimization techniques.
Ensure that our models run efficiently on various GPU architectures, supporting scalability for large-scale training.
Bachelor’s degree in Computer Science, Electrical Engineering, or a related field, with a focus on high-performance computing.
Strong programming skills in C++ and CUDA, essential for GPU optimization.
Experience with deep learning frameworks that support GPU acceleration, such as PyTorch or TensorFlow, crucial for model implementation.
Understanding of parallel computing concepts and GPU architecture, given the need to optimize for hardware constraints.
Familiarity with machine learning models, particularly generative models, to align optimizations with model needs.
Excellent problem-solving and debugging skills, necessary for addressing performance issues.
Competitive compensation and equity
401k (no match)
Healthcare (Silver PPO Medical, Vision, Dental)
Lunch and snacks at the office
We encourage you to apply even if you don't fully meet all the listed requirements; we value potential and diverse perspectives, and your unique skills could be a great asset to our team.
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Join Hedra as a Machine Learning Engineer (CUDA) in San Francisco, where we are at the forefront of generative media innovation. Backed by top investors like Index and A16Z, our mission is to redefine content creation through our groundbreaking Hedra Studio platform. As part of our passionate team, you will optimize cutting-edge machine learning models, specifically our 3DVAE and video diffusion models, harnessing the power of GPU hardware. Your primary responsibility will be to ensure our models perform efficiently by implementing CUDA programming for high-performance computing. Collaborating closely with research and engineering teams, you'll tackle performance bottlenecks and stay updated on the latest in GPU technology. We're looking for a candidate who has a background in high-performance computing and is proficient in C++ and CUDA, along with experience in deep learning frameworks like PyTorch or TensorFlow. At Hedra, we value self-starters who are ready to make an impact, and we appreciate diverse backgrounds and unique skills. Our workplace offers competitive compensation, benefits like healthcare, and a supportive environment for growth. If you're eager to push the boundaries of AI-driven content creation, we'd love to hear from you!
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