Prompt Engineering Intern
Skills
- Completed at least one upper-division machine learning course
- Previous applied ML or LLM-adjacent internship experience
- Hands-on experience with LLM agent graphs, LLM fine-tuning, or classical optimization algorithms
- Proficient in Python and ML frameworks (PyTorch/TensorFlow)
- Familiarity with model evaluation, benchmarking, and tooling for ML systems
- U.S. Person status required to access export-controlled data
- Bonus: experience with GIS/geospatial data and geospatial ML
Responsibilities
- Design and iterate prompts and agent graph architectures for LLM-driven wargaming workflows
- Implement and evaluate classical optimizers and non-LLM ML algorithms in the wargaming context
- Create benchmarks and geospatial-aware evaluation metrics for AI performance in mission scenarios
- Build test and evaluation tooling to measure LLM effectiveness, robustness, and failure modes
- Collaborate with cross-functional engineers, applied ML scientists, and military stakeholders
- Document experiments, results, and reproducible pipelines for handoff and scaling
- Ensure handling of export-controlled data in accordance with policy and team requirements
Education
- Must be a 3rd or 4th year undergraduate student, or a Master's or PhD student focusing on ML/AI
- At least one upper-division machine learning course completed
Benefits
- Comprehensive medical, dental, and vision plans (U.S. roles) with low employee cost
- Company-covered life and disability insurance; generous PTO and December holiday hiatus
- Family planning and parenting support including fertility and adoption assistance
- 24/7 mental health resources, therapy, and life coaching; additional wellness services
- Professional development reimbursement and career growth opportunities
- Commuter benefits and potential relocation assistance depending on role
- Retirement savings plans (401(k)/Roth and extended options for U.S. roles)
- Highly competitive equity grants typically included in full-time offers
Average salary estimate
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