
Deep Learning Software Engineer - R118
On-site
Fresh
Full-time
Computer Vision - Deep Learning/AI
Compensation
Salary undisclosedDescription
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
Who is Expedition Technology?
Expedition Technology (EXP) designs, develops, and delivers innovative solutions with national impact for the defense and intelligence communities. We use machine learning, artificial intelligence, and other advanced algorithms, platforms, and technologies to solve our customers' most complex, demanding and urgent C4ISR challenges. Our culture promotes individual growth and opportunity, prioritizes a collaborative team spirit, and invites the intellectually curious to solve challenging problems creatively. Headquarted in Northern Virginia's high-tech corrdor, EXP is a rapidly growing, privately held company that pushes the boundaries of what is possible every day.
To learn more about EXP and discover why we are an award-winning workplace, visit our web site and follow us on LinkedIn.
Interested in joining our team? Let’s explore together.
Join Our Team and Enjoy Exceptional Benefits!
Expedition Technology (EXP) offers a flexible, self-directed benefits package that is designed to fit your individual needs. Here’s a glimpse of the outstanding benefits you can enjoy when you join our team:
- Company-paid medical, dental, and vision insurance
- Generous Time Off: Enjoy 11 paid holidays, up to 34 days of PTO
- Robust 401(k) Plan: Benefit from up to a 12% company contribution, including a 3% safe harbor, 6% match, and up to 3% additional as a form of profit sharing.
- Student Loan Repayment: Take advantage of our unique option to reallocate a portion of your 401(k) match funds to repay student loans, helping you achieve financial freedom faster.
- Paid Parental Leave: Six weeks of paid leave for the primary caregiver and 2 weeks of paid leave for the secondary caregiver for you to bond with your new family member.
- Tuition Reimbursement: Pursue further education with up to $5,250/year available to support your continuous learning and growth.
- Referral Bonus Program: Earn rewards for bringing talented individuals into our team.
- Exclusive Entertainment Perks: Enjoy free tickets to sporting events, theater, concerts, and more, adding fun and excitement to your life.
- Onsite Amenities: Stay fit and healthy with our free, onsite fitness center, active workstations featuring treadmill and bike desks, and enjoy our onsite cafeteria with reduced-cost options.
- Inspiring Work Culture: Thrive in a collaborative, creative, and supportive culture where you are encouraged to push boundaries, take risks, and enjoy the rewards.
Join us and be part of a team that values your well-being and professional growth. Apply today and take the first step towards a fulfilling career with us!
EXP is proud to be an Equal Opportunity Employer that believes a diverse range of talent creates an environment that fosters creativity and innovation. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, genetic information, or protected veteran status.
Stack
Computer VisionPythonPyTorchCI/CDAWSMachine LearningDockerDeep LearningTensorFlow
- Posted
- Sep 22, 2026
- Last seen
- Sep 22, 2026
- First seen
- Sep 22, 2026