Applied AI Scientist

What you'll do

• Research, design, and develop large-scale foundation models for machine-generated data like logs and time series.
• Develop and enhance distributed training and inference workflows to improve model quality and scalability.
• Translate research ideas into production systems to address specific business and technical needs.
• Evaluate new AI/ML techniques and tools to solve technical challenges and support the team roadmap.
• Take ownership of assigned projects and proactively resolve technical obstacles to deliver high-quality results.
• Optimize model architectures and distributed training pipelines to minimize cost and latency.
• Implement MLOps practices including automated retraining, drift detection, and production monitoring.

What we're looking for

• Master Degree in Computer Science or a related quantitative field.
• 2+ years of industry research experience.
• 1+ year of experience in large-scale graph representation learning, GNNs, large language modeling, or multi-modal fusion.
• 2+ years of experience in Python and deep learning frameworks like PyTorch or TensorFlow.
• 1+ year of experience translating research ideas into production systems.
• Deep experience with graph transformers, spatio-temporal GNNs, and knowledge-graph-augmented modeling (preferred).
• Expertise in constructing and operating on large-scale graphs such as entity or service dependency graphs (preferred).
• Hands-on experience with frameworks like PyTorch Geometric, DGL, or GraphML systems (preferred).