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Senior Research Scientist

sciforium · San Francisco

New
Senior 🇬🇧 English
Python PyTorch JAX Flax XLA distributed training performance profiling speed optimization model serving inference optimization model compression diffusion models generative modeling

Job description

About the role

Sciforium is an AI infrastructure company developing next‑generation multimodal AI models and a proprietary, high‑efficiency serving platform. Backed by multi‑million‑dollar funding and direct sponsorship from AMD, the team is scaling rapidly to build the full stack powering frontier AI models and real‑time applications. The Senior Research Scientist will lead cutting‑edge research initiatives in large language models, generative media, model architecture, optimization, and scalable training systems.

Key responsibilities

  • Lead research in advanced machine learning areas such as LLMs, generative AI, diffusion models, and novel Transformer architectures.
  • Design, implement, and evaluate novel ML algorithms using frameworks like PyTorch and JAX.
  • Conduct large‑scale distributed training experiments on multi‑GPU/TPU systems.
  • Drive performance improvements through framework debugging, speed optimization, and training pipeline enhancements.
  • Produce high‑quality research output including papers, internal reports, patents, and reproducible code.
  • Collaborate with engineering and product teams to translate research prototypes into scalable production systems.

Required profile

  • PhD in Computer Science, Machine Learning, AI, Mathematics, or a related field.
  • 5+ years of academic or industry research experience (or exceptional fresh PhDs from top programs).
  • Proven track record of impactful research with publications in top‑tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, or ECCV.
  • Strong coding proficiency in Python with deep experience in PyTorch and/or JAX.
  • Experience with debugging, performance profiling, speed optimization, and distributed training at scale.

Required skills

  • Python
  • PyTorch
  • JAX (including Flax/XLA stack)
  • Distributed training on multi‑GPU/TPU systems
  • Performance profiling and speed optimization
  • Model serving, inference optimization, and model compression
  • Diffusion models and generative modeling

What we offer

  • Medical, dental, and vision insurance
  • 401(k) retirement plan
  • Daily lunch, snacks, and beverages
  • Flexible time off
  • Competitive salary and equity
  • Equal‑opportunity workplace

Questions fréquentes

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Source : ats:ashby

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Published 3 days ago

Expires 1 month from now

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sciforium

San Francisco