Sciforium builds the next generation of AI models with unprecedented efficiency, privacy, and versatility. Backed by SignalFire.
About the role
Sciforium is seeking a highly skilled Distributed Training and Inference Engineer to build, optimize, and maintain the critical software stack that powers our large-scale AI training and serving workloads. In this role, you will work across the entire machine learning infrastructure from low-level CUDA/ROCm runtimes to high-level frameworks like JAX and PyTorch to ensure our distributed training systems are fast, scalable, stable, and efficient.
What they're looking for
- 5+ years of industry experience in ML systems, distributed training, or related fields
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related technical fields
- Strong programming experience in Python, C++, and familiarity with ML tooling and distributed systems
- Deep understanding of profiling tools (e.g., Nsight, ROCm Profiler, XLA profiler, TPU tools)
- Deep expertise with partitioning configuration on the modern ML frameworks such as PyTorch and JAX
- Experience with multi-node distributed training systems and orchestration frameworks (DTensor, GSPMD, etc.)
More about this 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 with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications.
Sciforium is seeking a highly skilled Distributed Training and Inference Engineer to build, optimize, and maintain the critical software stack that powers our large-scale AI training and serving workloads. In this role, you will work across the entire machine learning infrastructure from low-level CUDA/ROCm runtimes to high-level frameworks like JAX and PyTorch to ensure our distributed training systems are fast, scalable, stable, and efficient.
This position is ideal for someone who loves deep systems engineering, debugging complex hardware–software interactions, and optimizing performance at every layer of the ML stack. You will play a pivotal role in enabling the training and deployment of next-generation LLMs and generative AI models.
Software Stack Maintenance: Maintain, update, and optimize critical ML libraries and...
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