Software Engineer – AI/ML

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with the team on research and development projects from the initial proposal stage through to the final wrap-up.

• Assess how R&D initiatives can utilize AI and machine learning models and products, aiming for their integration into partner DoD systems.

• Engage with vendors through Cooperative Research and Development Agreements (CRADAs) to provide valuable feedback on their products and solutions.

• Assist in enhancing the accuracy, safety, and compliance of vendor solutions with Branch requirements.

• Partner with external research collaborators in academia and industry to steer research projects towards their objectives.

• Work alongside research partners to develop solutions that deliver significant value to the Branch.

• Communicate effectively with both internal and external development teams using tools such as Teams, source control, ticketing systems, and code review platforms.

• Conduct Independent Verification and Validation (IV&V).

• Generate reports evaluating the effectiveness of models and techniques.

⛳️ Requirements

• Must be a U.S. Citizen with an active Secret Clearance (REQUIRED).

• Bachelor’s degree in a discipline related to AI and ML (such as Computer Science, Artificial Intelligence, Mathematics, Statistics, Data Science, etc.).

• 3-5+ years of directly relevant experience.

• Proficiency in Python, with experience in PyTorch, TensorFlow, or Scikit-learn, as well as Rust or Go.

• Ability to read, interpret, and adapt to code written by others across various styles and architectures.

• Proficiency in Git for version control.

• Experience in developing or applying classical machine learning models, particularly in computer vision and object classification.

• Familiarity with Large Language Models, including a comprehension of their internal structure and functionality, prompt engineering, debugging, and validation.

• Knowledge of reinforcement learning techniques.

• Experience with Agentic AI, including reprompting and classical agents.

• Knowledge of diffusion models applicable to images and other modalities.

• Experience with neuro-symbolic solutions that link classical or generative models to verifiable logic.

• Familiarity with adversarial AI/AI security aspects, including model poisoning, prompt injection, and model containment exploits.

• Experience with Explainable AI (XAI).

• Experience in deploying models and applications within containerized environments, utilizing Kubernetes or Docker.

• Strong understanding of the mathematical foundations underlying AI and ML.

• Capability to work with air-gapped, secure networks and execute models on them.

• Knowledge and experience in scaling down models for austere, low-resource environments.

• TS/SCI clearance is preferred.

• Real-world deployment experience is an advantage.

🏝️ Benefits

• Resources and support to help you thrive both personally and professionally.

• Employee-centric company that invests in the future of its employees.