About Us: Dunedain is building the world's most capable AI platform for Warfighters. Our mission is to unlock faster, smarter decision-making and actions at every echelon of the military by equipping service members with powerful, intuitive AI agents they can trust and control. From front-line units to the motor pool to the back office, our systems are already in the hands of operational units across the U.S. Army, transforming how data is accessed, interpreted, and acted upon. We combine frontier language models, retrieval systems, agentic workflows and intuitive end-user orchestration into mission-ready tools that work in disconnected, distributed, and classified environments. If you're passionate about building meaningful AI with real-world impact for the Warfighter, we want to work with you.
Role Overview: We're hiring a founding AI Software Engineer with a backend focus to lead the development of core AI infrastructure and model integration pipelines across our platform. You'll be responsible for building scalable backend systems to support LLM-based workflows, including fine-tuning, orchestration, and deployment into defense-grade environments. From training SLMs to managing MLOps pipelines and designing modular, production-grade AI services, you'll play a critical role in shaping the future of AI for military operations. This is a high-impact, full-time role with the option to work remotely or hybrid from our Austin, TX office.
Duties and Responsibilities- Design and implement machine learning architectures, with a focus on fine-tuning and training large language models (LLMs) for targeted applications.
- Develop and maintain ETL pipelines to support robust data ingestion, preprocessing, and feature engineering workflows.
- Lead model development efforts, including dataset curation, hyperparameter tuning, evaluation, and deployment of custom and pre-trained models.
- Establish and manage MLOps pipelines for reproducibility, scalability, and version control of data, models, and training processes.
- Monitor and evaluate model performance in production environments, implementing feedback loops and continuous improvement strategies.
- Apply knowledge of natural language processing (NLP) and generative AI to build task-specific models and components.
- Contribute to experimentation and R&D, including benchmarking models, testing new architectures, and staying current with advancements in the field.
- Ensure compliance with security, data governance, and ethical AI standards, especially in DoD environments.
- Document processes, experiments, and models to support collaboration, auditability, and knowledge sharing within the team.
Qualifications and Requirements- 3+ years of experience in machine learning or data science roles, with a focus on NLP and deep learning.
- Strong proficiency in Python and common ML frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
- Solid background in ETL pipeline development, data engineering, and working with structured/unstructured data at scale.
- Proficiency in MLOps practices, including model versioning, reproducibility, CI/CD pipelines for ML, and model monitoring.
- Experience with containerized ML environments (e.g., Docker, Kubernetes) and cloud-based architectures (AWS).
- Excellent documentation and communication skills to support cross-functional development and operational integration.
- US Citizenship & Secret and TS / SCI Security Clearances Eligible
Preferred Qualifications- Hands-on experience fine-tuning large language models (LLMs) using techniques like LoRA (Low-Rank Adaptation) or parameter-efficient fine-tuning.
- Familiarity with small language models (SLMs) and optimizing models for inference in resource-constrained environments.
- Proficiency in Geographic Information Systems (GIS), with the ability to integrate spatial data into machine learning workflows and support geospatial analysis.
- Experience deploying and maintaining ML models in air-gapped or secure environments, with an understanding of data movement restrictions and system constraints.
- Knowledge of DoD security frameworks, compliance standards, and working in secure computing environments is a strong plus.
Benefits:- Opportunity to impact the defense sector with innovative AI solutions alongside a fast-moving, passionate team.
- Flexible work arrangement (remote or hybrid).
- Competitive total compensation of $120,000 - $180,000 + .25 - 1.5% company equity, based on experience