AI/ML Engineer (Scenario Generation, Ontology & RAG)

PeopleTec, Inc.•Huntsville, AL

2d•Onsite

About The Position

PeopleTec is seeking an AI/ML Engineer in Huntsville, AL, to develop language-model applications for flight-simulator training, including scenario generation and doctrine question-and-answer capabilities. You will work with software engineers and an H-1 aviation subject matter expert to prepare training data, build retrieval-based applications, fine-tune models, and evaluate their performance for deployment.

Requirements

5–8 years of machine learning engineering experience, including delivery of language-model applications that retrieve information from documents, produce structured outputs, and use software tools.
Hands-on experience preparing training data and fine-tuning language models, including parameter-efficient methods and preference optimization using human feedback.
Strong Python skills and experience deploying models on local, CUDA-capable GPU systems.
Experience evaluating model performance and tracking experiments, model versions, and training-data history.
Experience building and evaluating retrieval-augmented generation (RAG) systems that produce reliable, expected results.
Ability to travel occasionally for test events.
Eligible for a Tier 3 background investigation and access to CUI; must maintain eligibility throughout employment.
Must be a U.S. Citizen

Nice To Haves

Experience with knowledge graphs and ontologies, including OWL, RDF, or SPARQL.
Experience integrating speech recognition and text-to-speech or working with audio pipelines for noisy environments.
Experience with schema-constrained generation or production model-serving adapters.
Experience in aviation, tactical training, or simulation.

Responsibilities

Build AI applications that generate training scenarios and answer questions using approved reference documents.
Prepare training data and fine-tune language models using domain material and instructor feedback.
Validate generated scenarios against training requirements and test model accuracy, response time, and safety.
Work with the software team to integrate, release, and maintain models and supporting data.
As capabilities expand, develop trainee assessment, adaptive difficulty, and after-action review features.