Startups · AI

Member of Technical Staff — Inference-Multimodal & Diffusion

RadixArk · Palo Alto, CA · On-site

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About RadixArk

RadixArk builds large-scale inference and training systems for the entire AI community, making frontier-level AI infrastructure open and accessible. Backed by Accel.

About the role

RadixArk is seeking a Member of Technical Staff — Inference-Multimodal & Diffusion to advance the frontier of generative modeling. You will work on cutting-edge diffusion and flow-based models for image, video, and multimodal generation, pushing model quality, efficiency, and scalability. This role combines deep research thinking with strong engineering execution — from designing novel algorithms to training and deploying models at scale.

What they're looking for

  • 5+ years of experience in ML research or applied ML engineering
  • Strong expertise in diffusion models or generative models (DDPM, DDIM, latent diffusion, flow matching, etc.)
  • Deep understanding of deep learning fundamentals and optimization
  • Proven experience training large-scale models on GPUs/TPUs
  • Strong proficiency in PyTorch or JAX
  • Experience implementing research ideas into working systems
More about this role

RadixArk is seeking a Member of Technical Staff — Inference-Multimodal & Diffusion to advance the frontier of generative modeling.

You will work on cutting-edge diffusion and flow-based models for image, video, and multimodal generation, pushing model quality, efficiency, and scalability. This role combines deep research thinking with strong engineering execution — from designing novel algorithms to training and deploying models at scale.

Your work will directly shape next-generation generative AI systems used by researchers, developers, and real-world applications.

This is a high-impact role for engineers and researchers who want to push the limits of generative models in both theory and practice.

5+ years of experience in ML research or applied ML engineering

Strong expertise in diffusion models or generative models (DDPM, DDIM, latent diffusion, flow matching, etc.)

Deep understanding of deep learning fundamentals and optimization

Proven experience training large-scale models on GPUs/TPUs

Strong proficiency in PyTorch or JAX

Experience implementing research ideas into working systems

Strong mathematical foundation in probability, statistics, and optimization

Ability to move...

Read the full posting on RadixArk's site ↗

Member of Technical Staff

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