Machine Learning Engineer (CUDA)

Join to apply for the Machine Learning Engineer (CUDA) role at Hedra

Join to apply for the Machine Learning Engineer (CUDA) role at Hedra

This range is provided by Hedra. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$150,000.00/yr - $250,000.00/yr

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. The Hedra team is fully in-person in SF/NY with a shared love of solving hard problems using whiteboards.
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.
Compensation Range: $150K - $250K

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Technology, Information and Internet

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