RadixArk
Member of Technical Staff — Inference-Multimodal & Diffusion
$200K–$400K
Palo Alto +1 · On-site · Staff · Full-time · Posted Feb 17, 2026
- Location
- Palo Alto
San Francisco - Experience
- 5+ years in ML research or applied ML engineering.
About the job
Develop and deploy diffusion and other generative models for image, video, and multimodal generation, improving their quality, efficiency, and scalability.
What you'll do
- Design and develop generative models and novel training and sampling methods.
- Optimize models for distributed training and collaborate on scaling training and inference.
- Evaluate models and translate research into production systems.
What they ask for
- Strong expertise in diffusion or generative models.
- Deep understanding of deep learning fundamentals, optimization, and mathematical foundations in probability and statistics.
- Proven experience training large-scale models on GPUs/TPUs.
- Strong proficiency in PyTorch or JAX and experience implementing research ideas in working systems.
Nice to have
- Publications in top-tier conferences such as NeurIPS, ICML, ICLR, or CVPR.
- Experience with distributed training, multimodal generation, transformer architectures, sampling efficiency, open-source projects, or scaling models to billions of parameters.
Pay
$200,000 - $400,000 USD annual base salary
Tools
DDPM, DDIM, latent diffusion, flow matching, GPUs/TPUs, PyTorch, JAX
AI focus
Research, train, optimize, and deploy diffusion, flow-based, and multimodal generative AI models.
Model-written summary · the original posting is authoritative