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# Senior / Principal Machine Learning Scientist, Scientific Reasoning Models, AI for Drug Discovery

- **Company:** Identity Digital
- **Location:** Palo Alto, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Distributed Systems, Machine Learning, Azure Machine Learning, Large Language Models, Data Pipelines
- **Published:** September 22, 2026
- **Apply:** https://nlppeople.com/apply/by7s

## About the Role

Strong Python engineering skills with end-to-end ownership experience.Hands-on experience with LLMs and agentic AI systems.Experience building or maintaining data pipelines / ML infrastructure.Experience with distributed systems or production-scale infrastructure.Familiarity with RL workflows or simulation environments.Ability to work independently in ambiguous, partner-facing environments.Comfortable working in high-security and high-reliability environments., Active U.S. security clearance or eligibility and willingness to obtain one.Experience supporting U.S. Government, defense, intelligence, or national security missions.Experience with defense/government-focused technology companies or startups.Background working in fast-moving startup, mission-critical government, or similar environments., Senior (5+ years of experience)

Tagged as: Industry, NLP, United States

## Description

We're looking for a strong AI Engineer to build and deploy applied AI systems from research and experimentation through production. This role combines LLM/agentic AI development, data pipelines, ML infrastructure, and production deployment in high-assurance, mission-critical environments. You'll also work directly with U.S. Government and strategic partners, translating real-world mission requirements into reliable AI systems., Build and deploy agentic AI systems supporting Government missions.Design LLM applications including multi-agent systems, tool-using agents, RAG, and human-in-the-loop workflows.Work directly with government partners to translate mission requirements into technical solutions.Build and maintain data curation, evaluation, and ML pipelines.Develop infrastructure for model inference, experimentation, evaluation, and deployment.Build AI systems that combine mission data, models, and tools to enable operational autonomy.Own systems end-to-end across architecture, development, deployment, reliability, security, and continuous improvement.


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