Jobs at Sciforium

The role involves optimizing and maintaining the software stack for large-scale AI training, focusing on CUDA/ROCm, JAX, and PyTorch to ensure efficiency and stability in distributed training systems.

Design, implement, and optimize custom GPU kernels (CUDA/ROCm, PTX, Triton/JAX Pallas) for large-scale LLM training and inference; profile performance, integrate kernels into PyTorch/JAX and internal runtimes, collaborate with researchers and hardware vendors, and build tooling, benchmarks, and testing for reproducible performance.

Develop the core systems for multimodal AI models, focusing on building model serving platforms and enhancing developer experience with tools and APIs.

The GPU Kernel Engineer will design and optimize GPU kernels for large-scale AI systems, integrating them into ML frameworks and collaborating across teams to enhance performance.

Develop the model serving platform for multimodal AI models, optimizing performance, collaborating with researchers, and ensuring reliable production infrastructure.

Lead advanced AI/ML research initiatives, developing novel algorithms and optimizing large-scale training systems. Mentor junior researchers and produce impactful research outputs.

As a Research Engineer, you'll work on pretraining, scaling, post-training, and deployment of AI models, improving infrastructure and performance.

The Data Scientist role involves creating and managing datasets for LLMs, developing high-throughput data processing scripts, and employing statistical analysis to ensure data quality and performance.

The Senior HPC & GPU Infrastructure Engineer maintains GPU compute clusters, leads system reliability, manages Linux environments, and optimizes ML infrastructure.