Job Title: Deep Learning Internship
Company: Deca Defense
Location: Remote
Employment Type: Unpaid Internship (20-25 hours per week)
ITAR Restriction: In order to comply with the International Traffic in Arms Regulations (ITAR), we can only accept applications from U.S. citizens. Applicants who do not meet this requirement cannot be considered for this position.
About Us:
Deca Defense exclusively serves Defense OEMs and the DoD, specializing in Edge AI engineering. Our mission is clear: eliminate warfighter pain points by developing custom AI models that directly resolve critical field challenges. We integrate embedded AI with advanced deep learning to deliver precise, mission-critical solutions at the tactical edge.
What sets Deca Defense apart is our AI engineering team, comprised of veterans who have transitioned from the battlefield to a critical capacity behind the scenes. These individuals bring irreplaceable real-world insights from varied deployments directly to our models. We deliver AI solutions tailored to the harsh realities of the tactical edge.
It’s that straightforward—while others build “one-size-fits-all, vendor-locked black-box solutions” that dazzle in demos and boost their stock prices, we’re busy engineering AI that excels where it truly matters: in the field, where mission success isn’t just a target, it’s a mandate.
Position Overview:
We’re offering an unpaid internship for a driven Deep Learning intern with a preference for candidates with a veteran background to join our team. This internship is designed to provide hands-on experience in deep learning techniques with a focus on solving real-world problems faced by warfighters. The ideal candidate will have a foundational understanding of deep learning and a desire to grow their skills in a collaborative, mission-driven environment.
Key Learning Opportunities and Responsibilities:
- Gain practical experience in developing and implementing deep learning models and algorithms tailored to address specific challenges in tactical applications with support and guidance from experienced professionals.
- Learn to use deep learning tools and frameworks such as TensorFlow and PyTorch for developing and training models, applying your theoretical knowledge in a hands-on environment.
- Enhance your programming skills by working primarily with Python, one of the most widely used languages in AI and deep learning.
- Acquire knowledge in quantization-aware training and post-quantization methods to improve model efficiency and performance, and apply these techniques under the supervision of our team.
- Work closely with cross-functional teams to understand project requirements and contribute to the delivery of innovative solutions, gaining experience in collaborative problem-solving.
- Learn how to optimize and fine-tune deep learning models for performance and scalability in real-world applications with mentorship from seasoned deep learning engineers.
- Conduct research to stay updated with the latest advancements in deep learning and AI, particularly in defense-related contexts, and apply your findings to ongoing projects.
- Participate in code reviews, testing, and debugging to ensure high-quality code, and develop your skills in maintaining robust, efficient codebases.
- Learn how to document processes, models, and results for future reference and knowledge sharing, contributing to the team’s collective expertise.
Preferred Qualifications and Learning Objectives:
- Preference for candidates with a military background, who can bring a unique perspective and understanding of warfighter challenges to the role.
- Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, with opportunities to apply and expand your academic knowledge in a practical setting.
- Basic familiarity with deep learning frameworks such as TensorFlow and PyTorch with opportunities to deepen your understanding through guided practical application.
- Experience with tools such as TensorRT, Vitis, and ONNX for model optimization and deployment is a plus with a focus on learning their application in real-world scenarios.
- Basic knowledge of neural networks, computer vision, NLP, or related areas with opportunities to learn and apply advanced techniques.
- Proficiency in Python programming, with support to further develop your coding skills in the context of deep learning.
- Familiarity with cloud platforms (AWS, Google Cloud, Azure) and distributed computing, with opportunities to learn more about their applications in AI.
- Strong problem-solving skills and attention to detail, with the chance to apply and refine these abilities in a supportive environment.
- Strong communication and collaboration skills, which you’ll have the opportunity to develop further while working with a multidisciplinary team.
- A plus if you have an understanding of military systems and warfighter needs, with opportunities to learn how these insights can be applied in AI and deep learning contexts.
Why Join Us:
- Join a team of seasoned veterans who have successfully transitioned from the field to the forefront of AI development. You’ll learn how deep learning solutions are engineered to directly impact mission success at the tactical edge.
- This internship offers you the chance to work on projects that address genuine challenges faced by warfighters, providing you with practical, impactful experience that goes beyond theoretical knowledge.
- Develop your skills in a dynamic environment, guided by professionals who’ve faced the challenges you’re helping to solve. Your growth and learning are prioritized, ensuring you gain valuable insights and expertise.
- We understand the demands of working at the tactical edge and offer the flexibility needed to support your learning journey. Our mission is to help you develop the skills and knowledge to excel in your career.
How to Apply:
If you are a veteran with a passion for deep learning and AI, and you meet the qualifications listed above, we would like to hear from you. Please note that this is an unpaid internship. Please submit your resume and a cover letter detailing your relevant experience and why you are interested in this position.