Member of Technical Staff — Diffusion Model
Listed on 2026-03-01
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IT/Tech
Data Scientist, Machine Learning/ ML Engineer, Artificial Intelligence, AI Engineer -
Engineering
Artificial Intelligence, AI Engineer
Member of Technical Staff — Diffusion Model About the Role
Radix Ark is seeking a
Member of Technical Staff — Diffusion Model 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.
Requirements5+ 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 from research prototypes to production-quality models
Strong PlusExperience with large-scale distributed training
Experience in multimodal generation (text-to-image, video, audio)
Familiarity with transformer architectures and hybrid models
Experience improving sampling speed and generation efficiency
Contributions to open-source generative model projects
Experience scaling models to billions of parameters
ResponsibilitiesDesign and develop next-generation diffusion and generative models
Improve model quality, cont rollability, and sample efficiency
Research and implement novel training and sampling methods
Optimize models for large-scale distributed training
Collaborate with systems teams to scale training and inference
Translate research ideas into practical production systems
Evaluate models using rigorous metrics and benchmarks
Contribute to long-term research and product direction in generative AI
About Radix ArkRadix Ark is an infrastructure-first AI company built by engineers who have shipped production AI systems, created SGLang (20K+ Git Hub stars, the fastest open LLM serving engine), and developed Miles, our large-scale RL framework.
We build world-class systems for training and inference and partner with frontier AI teams and cloud providers. Our mission is to democratize access to frontier AI infrastructure and models.
Our team has coordinated training across 10,000+ GPUs, optimized kernels serving billions of tokens daily, and supported leading AI research and production workloads.
Join us to build generative models that matter — at real scale.
CompensationWe offer competitive compensation with meaningful equity, comprehensive benefits, and flexible work arrangements. Compensation depends on location, experience, and level.
Radix Ark is an Equal Opportunity Employer and welcomes candidates from all backgrounds.
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