Machine Learning Engineer - Graph ML & Code Intelligence

IR Labs is an innovation lab focused on turning advanced AI research into production software quality products. The founding Machine Learning Engineer for Graph ML & Code Intelligence will lead the graph-learning roadmap, develop GNN and graph transformer models, build distributed training and inference pipelines, integrate graphs with language systems, and ship scalable graph services to production.

Responsibilities:

• Own the graph-ML roadmap end-to-end: turn research into production, balance SOTA with real-world constraints, and champion graph learning across teams
• Design and train modern GNNs/graph transformers; explore self-supervision, sparsity, and pretraining to lift retrieval, grounding, and reasoning
• Build high-performance training/inference pipelines on distributed GPUs with efficient sampling, mixed precision, and custom optimization where needed
• Fuse graphs with language systems to power retrieval and reasoning primitives across the product
• Model complex technical artifacts as graphs (e.g., code/IR or telemetry) and learn over them for analysis and optimization signals
• Ship low-latency, scalable graph services and APIs with streaming updates and robust SLAs
• Benchmark and harden sparse+dense kernels; instrument for performance, correctness, and reliability
• Establish ML/DataOps for large graphs (versioning, lineage, CI/CD) and embed security, privacy, and compliance by design; mentor and uplevel the team