Machine Learning Engineer (CUDA)

1 Month ago • All levels • Artificial Intelligence

Job Summary

Job Description

Hedra seeks a CUDA ML Engineer to optimize machine learning models (3DVAE and video diffusion models) for GPU performance. Responsibilities include developing efficient algorithms and data structures for GPU computation, working with research and engineering teams to identify and resolve performance bottlenecks, staying current with GPU technology advancements, and ensuring model efficiency across various GPU architectures. The ideal candidate will possess strong C++ and CUDA programming skills, experience with deep learning frameworks (PyTorch or TensorFlow), and a deep understanding of parallel computing and GPU architecture.
Must have:
  • C++ and CUDA programming
  • Deep learning frameworks (PyTorch/TensorFlow)
  • GPU optimization experience
  • Parallel computing & GPU architecture understanding
  • Generative model familiarity
Perks:
  • Competitive compensation and equity
  • 401k
  • Healthcare (Silver PPO Medical, Vision, Dental)
  • Lunch and snacks at the office

Job Details

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.

Overview:

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.

Responsibilities:

  • 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.

Qualifications:

  • 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.

Benefits:

  • 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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About The Company

We are a creation lab building foundation models into products that power the next generation of human storytelling

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