Machine Learning Engineer - Graph ML & Code Intelligence | Denver, CO (Remote & Flexible)

An innovative lab that builds AI-powered developer tools designed to autonomously understand, analyze, and repair complex software systems are looking for a Machine Learning Engineer to join their team.

What You'll Be Doing:

1. Own the graph-ML roadmap end-to-end by designing and training modern GNNs and graph transformers, modeling complex technical artifacts as graphs (code, IR, telemetry), and exploring self-supervision, sparsity, and pretraining to enhance retrieval, grounding, and reasoning capabilities
2. Fuse graphs with language systems to power retrieval and reasoning primitives, combining graph learning with LLMs/NLP for KG-augmented retrieval, entity linking, and grounding across the product stack
3. Build high-performance production infrastructure with distributed GPU training/inference pipelines, low-latency scalable graph services and APIs, efficient sampling and mixed precision optimization, and robust ML/DataOps for large graphs (100M–B+ edges) with versioning, lineage, and CI/CD
4. Ensure reliability and performance by benchmarking and hardening sparse+dense kernels, instrumenting for correctness and observability, embedding security, privacy, and compliance by design, and mentoring the team on graph learning best practices

What We're Looking For:

1. 8+ years delivering production ML
2. Proven impact combining graphs with LLM/NLP
3. Experience deriving graphs from complex sources (code, IR, telemetry) for analysis, optimization, or security use cases
4. Deep mastery of GNNs, geometric deep learning, graph theory, and practical graph querying
5. Strong systems expertise: C++/CUDA or equivalent; fluency in GPU/distributed training and performance tuning

What's In It For Me:

1. Remote & flexible
2. $180,000 - $210,000 base salary
3. Strong benefits package including Medical, Dental, Vision Insurance, 401k with Employer Contributions and more!

Apply now for immediate consideration!

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