We're seeking a skilled Software Engineer with strong AI skills to be the senior engineer driving our next-gen modeling initiative, from research prototype to production deployment across a modern AWS stack. Lead our graph-aware transformer that fuses omics signals with sample-level metadata to learn shared representations powering biomarker and target discovery.

We're seeking candidates with:

• 5+ years of hands-on ML/AI engineering (or equivalent impact), including shipping models to production.
• Deep proficiency in Python and PyTorch (or TensorFlow) with strong software engineering fundamentals.
• Experience building agentic workflows (LangGraph) that orchestrate data prep, model calls (Bedrock), and validation steps end-to-end.
• Strong background in transformers and at least one of: GNNs, contrastive/self-supervised learning, representation learning.
• Comfortable with GPU training stacks: CUDA, PyTorch AMP, profiling, memory/perf debugging.
• Familiarity with graph/data tooling: PyTorch Geometric, cuDF/cuGraph, NetworkX-equivalents.
• Practical AWS experience with at least some of: EC2, SageMaker, Bedrock, RDS (or similar managed DBs), and a managed/hosted graph database.
• Experience building reliable data/ML pipelines and evaluations at scale.