Machine Learning Engineer / SME (LLM Eval & RAG Testing) - SME | TS/SCI

Active TS/SCI required. U.S. citizenship required.

Location: On-site in McLean, VA (Full-Time).

Prove which LLMs actually work for the mission. You'll design RAG and LLM evaluation experiments, tune models on custom data, and run GPU-accelerated benchmarks so the team ships AI systems they can trust.

What you'll do

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

What you bring (required)

Active TS/SCI

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

Nice to have

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

Why Falls

A 9% retirement contribution, 100% of family medical premiums paid, and 4 weeks of PTO. We're a small business that's been delivering since 2019, so your work is visible and your voice counts.

Falls Technology is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability, or protected veteran status.