К содержимому

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

Falls TechnologyMcLean, VA 22101

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.

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