Machine Learning Engineer - Graph ML & Code Intelligence

IR Labs is seeking a Machine Learning Engineer to own the graph-ML roadmap from research to production. You will design and train GNNs and graph transformers, build high-performance pipelines, and integrate graphs with language systems for retrieval and reasoning. This role requires deep expertise in graph learning and strong systems engineering skills.

• Own the graph-ML roadmap end-to-end, turning research into production
• Design and train modern GNNs/graph transformers with self-supervision and pretraining
• Build high-performance training/inference pipelines on distributed GPUs
• Fuse graphs with language systems to power retrieval and reasoning primitives
• Model complex technical artifacts like code/IR or telemetry as graphs
• Ship low-latency, scalable graph services and APIs with streaming updates
• Benchmark and harden sparse+dense kernels for performance and correctness
• Establish ML/DataOps for large graphs with versioning, lineage, and CI/CD
• Mentor and uplevel the team

• 8+ years delivering production ML; 5+ years leading large-scale graph learning (100M–B+ edges)
• Deep mastery of GNNs/geometric DL, graph theory, and practical graph querying
• Proven impact combining graphs with LLM/NLP (e.g., KG-augmented retrieval, entity linking)