Member of Technical Staff — Inference-Multimodal & Diffusion

RadixArk; Palo Alto (CA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Competitive compensation

Meaningful equity

Comprehensive benefits

Flexible work arrangements

Job summary

A leading AI infrastructure company in California is seeking a Member of Technical Staff for Diffusion Model. This role involves designing cutting-edge generative models and collaborating with teams to optimize large-scale training processes. Candidates should have over 5 years of experience in machine learning, particularly with diffusion models, and proficiency in tools like PyTorch or JAX. This position offers competitive compensation, flexible work arrangements, and the opportunity to contribute to innovative generative AI systems.

Qualifications

• 5+ years of experience in ML research or applied ML engineering.
• Strong expertise in diffusion and generative models.
• Proven experience training large-scale models on GPUs/TPUs.
• 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.

Responsibilities

• Design and develop next-generation diffusion and generative models.
• Collaborate with teams to scale training and inference.
• Translate research ideas into practical production systems.
• 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.

Skills

ML research experience

Expertise in diffusion models

Proficiency in PyTorch or JAX

Mathematical foundation in probability

Experience training large-scale models

Research-to-production

Probability/Statistics/Optimization

Tools

PyTorch

JAX

Job description

Member of Technical Staff — Diffusion Model

About the Role

RadixArk is seeking aMember 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.

Requirements

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 from research prototypes to production-quality models

Strong Plus

Experience 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

Responsibilities

Design and develop next-generation diffusion and generative models

Improve model quality, controllability, 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 RadixArk

RadixArk is an infrastructure-first AI company built by engineers who have shipped production AI systems, created SGLang (20K+ GitHub 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.

Compensation

We offer competitive compensation with meaningful equity, comprehensive benefits, and flexible work arrangements. Compensation depends on location, experience, and level.

RadixArk is an Equal Opportunity Employer and welcomes candidates from all backgrounds.