Deep Learning Software Engineer

At Expedition Technology (EXP), we work on real‑world problems whose solutions will make an immediate impact on national security. If you desire an opportunity where you will apply your deep learning and software engineering expertise to challenging problems with no known solutions, EXP is the place to be! We are seeking an experienced Deep Learning‑and‑Software Engineer to join a dynamic team delivering novel solutions to our Intel Community. The role involves developing end‑to‑end deployable systems—from data sourcing and curation, through model building, training, and evaluation, to productizing final deliverables.

Responsibilities

• Research academic literature to stay current with the latest theories, techniques, and tools.
• Collaborate with a team to develop deep learning architectures and pipelines for novel applications.
• Implement solutions in Python using PyTorch.
• Deliver high‑quality, carefully tested software.
• Participate in team brainstorming sessions to shape innovative solutions.

Required Skills and Experience

• Active Top Secret clearance (TS/SCI preferred) and U.S. citizenship with eligibility to maintain a Top Secret or higher government‑issued security clearance.
• MS and 2+ years of experience, or BS and 4+ years of experience, in a technical field such as Computer Science, Electrical Engineering, Physics, Statistics, or Applied Mathematics.
• Proven proficiency in PyTorch, TensorFlow, or another modern machine‑learning framework.
• Solid theoretical understanding of deep neural networks, especially for computer‑vision applications (e.g., YOLO, Faster R‑CNN, Mask R‑CNN).
• Experience architecting, training, testing, and deploying machine‑learning solutions within an AWS environment.
• Familiarity with collaborative source‑code management tools (Git).
• Strong technical presentation and writing skills.
• Strong software development skills, including object‑oriented design and implementation in Python.
• Practical experience developing in both object‑oriented and procedural languages.
• Experience with standard data structures, algorithms, and application organization.
• Knowledge of the full software development lifecycle, CI/CD, and agile/scrum methodologies.
• Experience with software testing (unit, integration, functional, etc.).
• Exposure to software containerization with Docker, Linux, and cloud development.