Applied AI Research Engineer

About the role

We're building next-generation AI systems that help military planners explore, compare, and evaluate operational courses of action. Our work combines frontier language models, simulation, planning, and verification into human-in-the-loop decision-support systems for defense applications.

Responsibilities

• Design and build agentic AI systems for planning, decision support, and human-machine teaming
• Develop multi-agent workflows, fine-tune and evaluate models, build retrieval pipelines, experiment with post-training techniques, and integrate AI with simulation and planning software
• Work closely with AI researchers, software engineers, and defense experts to turn research ideas into production-ready capabilities
• Research areas of interest include human-machine teaming for AI-assisted course-of-action development, comparison, critique, refinement, and operational decision support; agentic planning systems that integrate language models with simulation, doctrine retrieval, external tools, structured outputs, and deterministic verification; adapting and optimizing foundation models through fine-tuning, post-training, distillation, reinforcement learning, and rigorous evaluation for planning and decision-support tasks; multi-agent AI systems for Red/Blue planning, control-cell support, adjudication, branch-and-sequel analysis, and collaborative planning workflows; building reliable AI systems using self-correction, structured reasoning, constraint-aware generation, verification, and robust tool use; learning from human expertise through planner feedback, preferences, approvals, synthetic data generation, and human-in-the-loop improvement; trustworthy AI for high-consequence applications, with an emphasis on explainability, provenance, traceability, auditability, uncertainty estimation, and model behavior analysis

Requirements

• Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, Mathematics, Physics, or a related technical field, or equivalent practical experience
• 3+ years building AI, machine learning, or applied research systems
• Strong Python engineering skills
• Experience with PyTorch and modern LLM tooling (Transformers, vLLM, Hugging Face, etc.)
• Experience building or deploying agentic AI systems, tool-calling workflows, or multi-step reasoning pipelines
• Experience fine-tuning, evaluating, or serving language models
• Experience with retrieval-augmented generation, embeddings, vector search, or knowledge retrieval systems
• Strong understanding of experiment design, benchmarking, and model evaluation
• Ability to move quickly from research prototype to production-quality implementation

Qualifications

• Eligible to obtain a U.S. security clearance

Skills

• Strong understanding of experiment design, benchmarking, and model evaluation
• Ability to move quickly from research prototype to production-quality implementation

Benefits

• Pay depends on experience, but we strive to be at the upper end of the salary range
• Health care plan with 100% premium coverage, including medical, dental, and vision
• 401k with 5% matching
• Paid Time Off (uncapped vacation, plus sick and public holidays)
• Flexible hybrid or remote work arrangement
• Relocation assistance for qualifying employees

Pay

Wage Transparency - The salary range for this role is not a guarantee of compensation or salary, as the final offer amount may vary based on factors including, but not limited to, individual proficiency, skills, experience, and location. We are an equal opportunity employer.