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Serverless LLM serving and multimodal foundation models

GPU Kernel Engineer

Sciforium is an AI infrastructure company developing multimodal AI models and a high-efficiency serving platform. The company is seeking a GPU Kernel Engineer to design and optimize custom GPU kernels, integrate them into machine learning frameworks, and improve performance for large-scale AI training and inference. The role involves collaborating across hardware, systems, research, and model-serving teams to optimize compute performance.

Pre-training Research Engineer

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary high-efficiency serving platform. The Pre-training Research Engineer will implement, scale, and improve byte-native and multimodal foundation models while developing production-grade training code and infrastructure. The role focuses on model architecture, training objectives, optimization, scaling experiments, and analysis of model behavior and quality.

Data Center Real Estate & Development Specialist

Sciforium is an AI infrastructure company developing multimodal AI models and a proprietary serving platform. The Data Center Real Estate & Development Specialist will own data center capacity from site sourcing and technical diligence through lease negotiation, facility conversion, permitting, procurement, and construction execution. The role coordinates brokers, landlords, utilities, engineering firms, contractors, hardware vendors, and internal stakeholders while managing schedules, budgets, risks, and deployment readiness.

Sciforium is an AI infrastructure company developing multimodal AI models and a high-efficiency serving platform. The GPU Kernel Engineer will design, implement, and optimize custom GPU kernels for large-scale AI training and inference, integrate them into machine learning frameworks, and improve performance across the hardware–software stack. The role also involves profiling workloads, collaborating with researchers and systems teams, and working with GPU hardware vendors.

Research Engineer - Model Evaluation & MLOps

Sciforium is an AI infrastructure company developing multimodal AI models and a high-efficiency serving platform. The Research Engineer will build tools and infrastructure to evaluate, deploy, and operate multimodal foundation models, automate benchmarking, and improve MLOps workflows connecting research experiments to reliable releases.

GPU Cluster Engineer, Systems & Platform

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. They are seeking a GPU Cluster Engineer to own the software stack of GPU clusters, ensuring high-performance infrastructure for model training and serving teams.

Senior AI Serving Engineer, Backend

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. The role involves building the model serving platform and collaborating with ML researchers to integrate new multimodal models into production workflows while ensuring high performance and reliability of production services.

Distributed Training Engineer

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. The Distributed Training Engineer will build, optimize, and maintain the software stack for large-scale AI training workloads, ensuring systems are fast, scalable, and efficient.

Lead Software Engineer, Model Serving Platform

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. The Lead Software Engineer will architect and lead the development of the model serving platform, guiding and mentoring other engineers while building core components and collaborating with ML researchers.

Distributed Training and Inference Engineer

Sciforium is an AI infrastructure company developing multimodal AI models and a high-efficiency serving platform for frontier AI applications. The Distributed Training and Inference Engineer will build, optimize, and maintain the ML software stack across CUDA/ROCm runtimes, JAX, and PyTorch, while improving distributed training and serving performance, reliability, and scalability.