Research Engineer - Applied AI

Granica is an AI research and infrastructure company focused on reliable, steerable representations for enterprise data. The role involves transforming research ideas into practical algorithms and production-ready systems, optimizing learning methods for structured AI, and collaborating across teams to integrate algorithms into the core data platform.

Responsibilities:

• Transform foundational ideas from Granica Research and Prof. Andrea Montanari’s group into scalable algorithms and experimental prototypes
• Build the evaluation harnesses, metrics, and datasets that reveal real signal from research concepts
• Define and refine the metrics that determine progress in structured AI
• Develop efficient learning methods for relational, tabular, graph, and enterprise data
• Prototype representation learning architectures and compression-aware models for large-scale structured information
• Implement fast training and inference loops using PyTorch, JAX, or custom kernels
• Optimize memory, compute, and data-movement paths with a focus on cost, latency, and throughput
• Design hybrid learning systems that reason over structured data natively, not through text intermediaries
• Work with Research Scientists to validate hypotheses at scale
• Work with Systems Engineers to integrate your algorithms into Granica’s core data platform
• Work with Product Engineering to ship features that power live enterprise workloads
• Run controlled experiments, analyze performance deltas, and deliver results with clear benchmarks
• Drive the loop from prototype to production, improving the system each cycle