✦ Luna Orbit — AI & Machine Learning

Software Engineer/Developer

at Noblis

📍 Remote, US Remote 💰 $105K – $164K USD / year Posted April 15, 2026
Salary $105K – $164K USD / year
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

Software Engineer/Developer role supporting NASA Aeronautics and Exploration Technology programs focused on NLP and LLMs. You will build systems to extract, store, and interpret structured aviation data, digitize airspace constraints into Exchange Model (XM), and automate NOTAM conversion.

  • Benchmark automation for classification documents and LOA digitization
  • Develop natural language understanding models to extract operational information
  • Demonstrate utility of fine-tuned large language models on aviation data
  • Streamline digitization of operational information from OIS webinars using state-of-the-art AI/NLU
  • Draft and comment on final reports for FAA deliverables and present at peer-reviewed conferences

The technical work centers on modern data analytics and machine learning, especially natural language processing (NLP) and natural language understanding (NLU) using fine-tuned large language models (LLMs). You will implement automation and digitization pipelines for legacy SOP/LOA documents into structured data formats (Exchange Model (XM)) and convert Notice to Airmen (NOTAM) into digital representations for proactive maintenance/risk reduction.

The ideal candidate is a mid-level software engineer/developer with strong experience building natural language processing (NLP) and natural language understanding (NLU) systems using large language models (LLMs), including task fine-tuning for structured data extraction. They have hands-on experience digitizing and transforming aviation documents into digital formats (e.g., LOA/SOP-derived constraints and NOTAM conversion), and can communicate results through final reports and peer-reviewed presentations.

Natural language processing (NLP)Natural language understanding (NLU) using large language models (LLMs)Fine-tuning large language modelsDigitization and extraction of airspace constraints in Exchange Model (XM)Automating conversion of Notice to Airmen (NOTAM) into digital formatDraft and comment on final reports for project deliverables to FAAPresent innovations in natural language processing and understanding at peer reviewed conferenceCross-functional collaboration for software delivery timelines and quality standards
Exchange Model (XM)Notice to Airmen (NOTAM)Natural language processing (NLP)Large language models (LLMs)
natural language processing (NLP)natural language understanding (NLU)large language models (LLMs)fine-tuningExchange Model (XM)Notice to Airmen (NOTAM)digitizationstructured data extractiondata analyticsmachine learning technologiesbenchmark automation
Benchmark automationClassification documentsNatural language understanding (NLU) modelsLarge language models (LLMs)Fine-tuning large language modelsNatural language processing (NLP)Task fine tuningInfo-centric National Airspace System (NAS)Large language model (LLM) streamliningOperationally significant information extractionStructured data extractionStructured data storageStructured data interpretationPost-operational analysisDigitization and extraction of airspace constraintsExchange Model (XM)Legacy Standard Operating Procedures (SOP)Letter of Agreement (LOA)Notice to Airmen (NOTAM)Digital format conversionProactive maintenance/risk reductionData-driven recommendationsSoftware delivery alignment with project timelinesSoftware delivery alignment with quality standardsDrafting final reports for project deliverables to FAAPeer reviewed conference presentationsCross-functional collaborationMachine learning technologies
Cross-functional collaborationTechnical leadershipMentorshipGuidance to junior team membersCustomer-facing communicationCollaboration with cross-functional teamsInnovation mindsetCollaborative problem-solvingStakeholder communicationIndependent problem resolution
Industry Aerospace
Job Function Build and prototype NLP/LLM systems to digitize and extract structured aviation airspace data for NASA
Role Subtype NLP Engineer
Tech Domains AI & Machine Learning, Natural language processing (NLP), Data & Analytics, Aerospace
Software Engineer/DeveloperSoftware EngineerSoftware DeveloperNoblisNational Aeronautics and Space Administration (NASA)NASA Ames Research Center (ARC)AeronauticsExploration TechnologyAdvanced Methods projectInfo-centric National Airspace System (NAS)natural language processing (NLP)natural language understanding (NLU)large language models (LLMs)fine-tuningExchange Model (XM)Notice to Airmen (NOTAM)Standard Operating Procedures (SOP)Letter of Agreement (LOA)data analyticsmachine learning technologiesbenchmark automationpeer reviewed conferenceFAAdraft and comment on final reports

Must be able to implement natural language processing (NLP) / natural language understanding (NLU) with large language models (LLMs) and fine-tuning, Must have demonstrated experience with digitization/extraction workflows using Exchange Model (XM) and Notice to Airmen (NOTAM) automation

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