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HomeCompaniesRadixArkMember of Technical Staff — Diffusion Model

Member of Technical Staff — Diffusion Model

RadixArk · Palo Alto, CA · Hybrid · Active · Greenhouse

Job facts

FieldValue
CompanyRadixArk
TitleMember of Technical Staff — Diffusion Model
Normalized title-
Department / teamEngineering
LocationPalo Alto, CA, United States
Work modelHybrid / Hybrid
Employment type-
Salary-
Statusactive
ATS providerGreenhouse
Posted / first seen2026-02-17 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-22

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PageWhat it containsOpen
Company jobsActive postings from RadixArk.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Palo Alto.Open
Department jobsActive postings in Engineering.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyRadixArk
Source59272e4b-3a76-45c5-8439-e3f3e221c87a
ATS providerGreenhouse

Description

About the Role RadixArk 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. 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 Publications in top-tier conferences (NeurIPS, ICML, ICLR, CVPR, etc.) 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 company built by engineers who've shipped production AI systems, created SGLang (20K+ GitHub stars, the fastest open LLM serving engine), and developed Miles (our large-scale RL framework). We're on a mission to democratize frontier-level AI infrastructure by building world-class open systems for inference and training. Our team has optimized kernels serving billions of tokens daily, designed distributed training systems coordinating 10,000+ GPUs, and contributed to infrastructure that powers leading AI companies and research labs. We're backed by well-known infrastructure investors and partner with Nvidia, Google, AWS, and frontier AI labs. Join us in building infrastructure that gives real leverage back to the AI community. Compensation We offer competitive compensation with meaningful equity, comprehensive benefits, and flexible work arrangements. Compensation depends on location, experience, and level. Equal Opportunity RadixArk is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Full job record

Job IDd8f2729f50657b310542abfd91ff641e65797674
Org ID24beb46a-d8dc-42c5-a58a-e4f927f45491
Source ID59272e4b-3a76-45c5-8439-e3f3e221c87a
Board ID59272e4b-3a76-45c5-8439-e3f3e221c87a
Providergreenhouse
Provider Job Key4134889009
TitleMember of Technical Staff — Diffusion Model
Normalized Title
Statusactive
Activeyes
Location TextPalo Alto, CA
DepartmentEngineering
Team
Employment Type
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CityPalo Alto
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://job-boards.greenhouse.io/radixark/jobs/4134889009
Apply URLhttps://job-boards.greenhouse.io/radixark/jobs/4134889009
First Seen At2026-05-29 22:58:18Z
Last Seen At2026-06-22 07:40:43Z
Last Checked At2026-06-22 07:40:43Z
Last Changed At2026-05-29 22:58:18Z
Inactive At
Source Posted At2026-02-17 10:33:07Z
Source Updated At2026-05-23 01:09:16Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=radixark/date=2026-06-22/2026-06-22T07-40-43-761Z-844389343170b06955b8ea30d7212bbb1585a66d016c46be8f25ebceb1ab15a0.json
Event Fields
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Parsed Structured
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Extensions
{}
Native Structured
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