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!
Currently, we are seeking an experienced Deep Learning-and-Software Engineer who will work with a dynamic team that is delivering novel solutions to our Intel Community. We’re looking for someone who has in-depth understanding of DL architectures such as YOLO, Faster R-CNN, Mask R-CNN, and other state of the art object detection models. The candidate should feel comfortable developing and testing end-to-end deployable systems; from sourcing and curating data, building, training, and evaluating models, to productizing final deliverables.
If you feel fulfilled by rolling up your sleeves and thinking about hard problems, building and integrating learning-based algorithms and systems, and delivering robust solutions in a fast paced but scientifically rigorous environment, we want to hear from you!
Interested in joining our team? Here’s what you’ll need to succeed:
Responsibilities include:
- Researching academic literature to keep abreast of the latest theories, techniques, and tools
- Working in a team to develop deep learning architectures and pipelines for novel applications
- Implementing solutions in Python (PyTorch)
- Delivering high-quality, carefully tested software
- Participate in team brainstorming sessions to shape innovative solutions
Required Skills and Experience:
- An active Top Secret clearance (TS/SCI preferred)
- US Citizenship – must be eligible to maintain a US-Government issued security clearance of Top Secret or higher
- 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 other modern machine learning framework
- Solid theoretical understanding of deep neural networks as well as its applications, particularly in computer vision
- Proven experience architecting, training, testing, and deploying machine learning solutions within an AWS environment
- Experience using collaborative source code management tools (Git)
- Strong technical presentation and writing skills
- Strong software development skills to include object-oriented design and implementation in languages like Python
- Strong practical experience developing in both object oriented and procedural languages
- Experience with standard data structures, algorithms, and application organization
- Experience with the full software development lifecycle, CI/CD, agile/scrum methodologies
- Experience with software testing (unit, integration, functional, etc.)
- Exposure to software containerization with Docker, Linux, and cloud development