IFM
Eval360 - Error Analysis Engineer
About this role
Join the Institute of Foundation Models as an Error Analysis Engineer to develop systems that evaluate and improve foundation models. You'll work with a multidisciplinary team to identify failure modes, measure model quality, and enhance the safety and reliability of AI systems.
What you'll do
- Analyze errors and failure modes in foundation models
- Develop evaluation systems to measure model quality and performance
- Collaborate with researchers and ML engineers on model improvement strategies
- Support risk assessment and safety evaluation of frontier models
- Contribute to model governance and deployment readiness frameworks
- Work with product teams to translate research into impactful systems
What they're looking for
- Error analysis and debugging methodologies
- Machine learning evaluation techniques
- Data analysis and statistical reasoning
- Python or similar programming languages
- Foundation models knowledge
- Research and problem-solving abilities
- Cross-functional collaboration
- AI safety and model assessment
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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
- Can you describe your experience with error analysis or failure mode identification in machine learning models?
- How have you approached systematizing and categorizing different types of model errors or behavioral issues you've observed?