About the roleSciforium is seeking an exceptional Senior Research Scientist specializing in advanced AI/ML to push the boundaries of scientific and engineering innovation. In this role, you will lead cutting-edge research initiatives in large language models, generative media, model architecture, optimization, and scalable training systems. You will work hands-on with modern ML frameworks, contribute original research, and collaborate with engineering teams to bring impactful models into production. This role is ideal for a highly motivated researcher who is passionate about driving foundational breakthroughs in AI.
What you'll do- Lead research in advanced machine learning areas such as LLMs, generative AI, foundational modeling, optimization techniques, 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 using multi-GPU/TPU systems and modern compute infrastructure.
- 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.
- Stay ahead of the latest research developments and integrate state-of-the-art techniques into Sciforium's AI roadmap.
- Mentor junior researchers and contribute to building a world-class AI research culture.
Ideal candidate profile- PhD in Computer Science, Machine Learning, AI, Mathematics, or a related field (required).
- 5+ years of academic or industry research experience (with flexibility for exceptional fresh PhDs from top programs).
- Proven track record of impactful research, evidenced by publications in NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or similar top-tier venues.
- Strong coding proficiency in Python, with deep experience in PyTorch and/or JAX.
- Experience with debugging, performance profiling, and speed optimization.
- Expertise in distributed training at scale.
Nice-to-have- Extensive experience with JAX/Flax/XLA stack
- Experience with efficient model serving, inference optimization, model compression, or production ML systems.
- Hands-on research or engineering experience with diffusion models or generative modeling.
- Experience contributing to product development or collaborating with cross-functional engineering teams.
- Open-source contributions to major ML frameworks or libraries.
Benefits include- Medical, dental, and vision insurance
- 401k plan
- Daily lunch, snacks, and beverages
- Flexible time off
- Competitive salary and equity
