LLM Training Engineer

About the Company

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.

Responsibilities

• Work across the full foundation-model stack including pretraining, scaling, and post-training
• Develop post-training pipelines such as SFT, preference optimization, and RLHF/RLAIF
• Build scalable sandbox environments for agent evaluation and learning
• Optimize inference throughput and latency for byte-native architectures
• Profile and optimize GPU kernels, runtime bottlenecks, and memory behavior
• Design stable training recipes and scaling laws for novel architectures

Requirements

• Strong general software engineering skills for writing robust, performant systems
• Experience with training or serving large neural networks (LLMs or similar)
• Solid grasp of deep learning fundamentals and modern literature
• Comfort working in high-performance environments like GPU and distributed systems
• MS or PhD in Computer Science, Machine Learning, AI, Mathematics, or a related field

Preferred Qualifications

• Experience with large-scale distributed training (FSDP, ZeRO, or Megatron-style systems)
• Experience building RL environments, simulators, or agent frameworks
• Expertise in inference optimization, model compression, or quantization
• Experience building large ETL pipelines for internet-scale data ingestion
• Strong experimental hygiene including ablations, metrics, and reproducibility

Benefits

• Medical, dental, and vision insurance
• 401k plan
• Daily lunch, snacks, and beverages
• Flexible time off
• Competitive salary and equity