Pre-training Research Engineer

Job description

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 role** As 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 Responsibilities** ### **Pre-training & Scaling** - Train 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. ## **Must-Haves** - **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. ## **Nice-to-Haves** - **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. ### **Education** - MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field. ## **Benefits include** - Medical, dental, and vision insurance - 401k plan - Daily lunch, snacks, and beverages - Flexible time off - Competitive salary and equity ## **Equal opportunity** 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.