Machine Learning Engineer, Applied AI
Core
Building agent-native operating systems for regulated institutions (construction, insurance, health) to automate complex workflows like permitting and claims processing.
Role type
Senior IC machine learning engineer (applied AI, agentic systems)
Builds
Production decision systems, composite AI pipelines, and agent-based workflows for government, insurance, and health sectors.
Domain
Applied AI, institutional automation, regulated industries (construction, insurance, healthcare)
Deliverable
production ML models
Required skills
LLMs and agentic systems, fine-tuning, prompt engineering, tool use, reasoning, vision transformers, segmentation models, VLMs, rule engines, evaluation design, data pipeline engineering
Preferred skills
RL fine-tuning, composite system architecture, failure-mode taxonomy design
Technologies
LLMs, vision transformers, segmentation models, VLMs, rule engines
Responsibilities
Define ML problems from ambiguous customer needs, own AI systems end-to-end from training to production, work directly with institutional stakeholders, engineer for production constraints (accuracy, latency, cost), build rigorous evaluation suites
Seniority
Senior, hands-on IC