IFM
Machine Learning Engineer – World Model
About this role
Join a research lab at MBZUAI's Institute of Foundation Models to develop ML infrastructure and MLOps systems for cutting-edge world model research. You'll design scalable cloud systems that enable researchers to conduct experiments and advance next-generation AI capabilities.
What you'll do
- Design and operate scalable cloud infrastructure for ML research and experimentation
- Build and maintain data pipelines for model training and evaluation
- Develop MLOps systems to support researcher workflows
- Ensure reliability, observability, and performance of research infrastructure
- Collaborate with researchers and engineers on infrastructure requirements
- Support deployment and scaling of foundation model experiments
What they're looking for
- Cloud infrastructure and DevOps
- MLOps and ML systems design
- Data pipeline engineering
- Python and software engineering
- Distributed systems and scaling
- Infrastructure as Code
- Monitoring and observability tools
- Problem-solving and collaboration
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IFM
Institute of Foundation Models conducts research on large-scale foundation models, diffusion-based language models, and world models, building the distributed training infrastructure and MLOps systems required for cutting-edge AI development. The company is hiring research scientists, ML infrastructure engineers, and systems developers to optimize pre-training frameworks, scale distributed training across multi-GPU clusters, and advance inference and experiment capabilities.
View all jobs at IFMLikely interview questions
- Describe your experience designing and deploying ML infrastructure at scale. What challenges have you encountered with distributed training, and how did you solve them?
- Tell us about a time you built data pipelines for machine learning research. How did you ensure reliability and observability?