Salary
≈ $131k – $292k per year (Estimated)
Location
In office (McLean)
Employment
Full-Time
First seen by Alion on Oct 28, 2026.
Overview
Company
Impact
Profile match
Falls Technology delivers software engineering, enterprise modernization, DevSecOps, and AI-enabled solutions supporting federal and national security missions.
Falls Technology LLC is hiring a Machine Learning Engineer / SME to evaluate and validate LLM-based systems, including RAG, for mission use. The role designs benchmarks and experiments, tunes models on custom data, and builds AI/ML systems using GPU-accelerated computing.
Responsibilities
- Test, evaluate and validate AI systems with a focus on LLM-based systems (including RAG testing)
- Design and run experiments that benchmark LLMs against defined measures
- Tune neural networks / LLMs on custom datasets and apply results to concrete use cases
- Build AI/ML models and ensembles in Python or R (library selection, preprocessing, model assessment)
- Use deep learning frameworks such as PyTorch, TensorFlow or Keras
- Leverage GPUs for accelerated training and evaluation
- Write solid SQL (CTEs, set operations, aggregates, nested subqueries) against analytical datasets
- Work in GitHub and Jenkins-style CI for reproducible experiments
- Communicate methodological choices and model results to technical and non-technical stakeholders
Skills
- Active TS/SCI required
- U.S. citizenship required
- Hands-on RAG testing experience (must-have)
- Tuning neural nets / LLMs on custom datasets for real use cases
- Building AI/ML models and ensembles in Python or R
- PyTorch, TensorFlow or Keras (key)
- GPU-accelerated computing (key)
- Testing, evaluating or validating LLM-based AI systems (key)
- Experiment design to benchmark LLMs (key)
- SQL including CTEs, set ops, aggregates and nested subqueries
- GitHub and Jenkins (or equivalent) version control / CI
- Hugging Face Transformers library and hub
- Building benchmarks that measure LLM performance
- Cloud computing development and architecture
- Flask or similar front-end/web frameworks
- Text classification and topic modeling (scikit-learn or deep learning)
- Semantic search applications
- Tableau dashboards
- Verification/validation test benches, Explainable AI (XAI), ONNX
Benefits
- A 9% retirement contribution
- 100% of family medical premiums paid
- 4 weeks of PTO
Company Overview
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