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.
About the roleAs a Pre-training Research Engineer, you’ll focus on model implementation, pertaining and scaling, and improving the quality of our byte-native and multimodal foundation models. You’ll build and iterate quickly on research ideas, contribute production-grade training code and infrastructure, and help deliver high-quality base models that can serve real-world use cases at scale.
Key ResponsibilitiesPre-training & ScalingTrain large byte-native and multimodal foundation models across massive, heterogeneous corpora.
Implement and evaluate new model architectures, training objectives, and optimization methods.
Develop stable pre-training recipes and run scaling experiments for novel architectures.
Conduct ablations and analyze training dynamics, model behavior, and base-model quality.
Work with data and distributed training engineers to improve training efficiency, reliability, and scalability.
5+ years of experience in machine learning research or engineering, with a proven track record of developing and pre-training large language or multimodal foundation models.
Software Engineering: Strong general software engineering skills, with the ability to write robust and performant training code.
ML Foundations: Solid understanding of deep learning fundamentals and modern pre-training methods and literature.
Research and Experimentation: Ability to quickly implement research ideas and evaluate them using clear baselines, ablations, metrics, and analysis.
GPU and Distributed Training: Hands-on experience running training workloads in GPU-based environments, with familiarity with distributed training.
Education: MS in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field.
PhD in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field.
JAX Ecosystem: Extensive experience with the JAX, Flax, and XLA stack.
Large-Scale Distributed Training: Experience with multi-node pre-training using systems such as FSDP, ZeRO, or Megatron.
Training Recipes and Scaling: Experience developing training recipes, ablations, or scaling experiments.
Monitoring and Reproducibility: Experience owning end-to-end training and evaluation pipelines with monitoring and reproducibility.
MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field.
Medical, dental, and vision insurance
401k plan
Daily lunch, snacks, and beverages
Flexible time off
Competitive salary and equity
Sciforium is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Skills Required
- 5+ years of experience in machine learning research or engineering, including developing and pre-training large language or multimodal foundation models
- Strong general software engineering skills and ability to write robust, performant training code
- Solid understanding of deep learning fundamentals and modern pre-training methods and literature
- Ability to implement research ideas and evaluate them with baselines, ablations, metrics, and analysis
- Hands-on GPU-based training experience and familiarity with distributed training
- MS in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field
- PhD in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field
- Extensive experience with the JAX, Flax, and XLA stack
- Experience with multi-node pre-training using FSDP, ZeRO, or Megatron
- Experience developing training recipes, ablations, or scaling experiments
- Experience owning end-to-end training and evaluation pipelines with monitoring and reproducibility
What We Do
Sciforium is pioneering the future of AI infrastructure and research. Backed by AMD and SignalFire, we're developing byte-native multimodal foundation models while delivering serverless LLM serving at a fraction of traditional costs.
