Job Title: Data Scientist & Data Generation Internship
Company: Deca Defense, LLC
Location: Remote
Employment Type: Unpaid Internship (20-25 hours per week)
ITAR Restriction: 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 motivated Data Scientist & Data Generation intern with a preference for candidates with a military background. This role will provide hands-on experience in data science, AI model training, and synthetic data generation, all while contributing to real-world projects that address critical warfighter challenges. The ideal candidate will have a strong interest in data science and a desire to grow their skills through practical experience and mentorship from experienced professionals.
Key Learning Opportunities and Responsibilities:
- Data Collection & Generation: Gain experience in generating synthetic datasets, as well as collecting and curating real-world data to train machine learning models that address tactical edge applications.
- Data Preprocessing: Learn how to preprocess, clean, and structure raw data for machine learning applications, improving your ability to handle unstructured and complex data efficiently.
- Feature Engineering: Enhance your skills in feature extraction and engineering, learning how to create meaningful variables that drive better AI model performance in defense scenarios.
- Model Training: Work closely with our team to train, validate, and fine-tune machine learning models using the data you’ve prepared, applying your theoretical knowledge in a real-world defense context.
- Data-Driven Insights: Assist in analyzing data and extracting actionable insights, learning how to effectively communicate results and model performance to non-technical stakeholders.
- Synthetic Data: Learn to use modern data generation tools and techniques to create synthetic datasets that simulate real-world environments, vital for training models in situations where data is limited or unavailable.
- Collaboration: Work with AI engineers and system experts to understand project requirements and contribute to the development of scalable AI solutions, fostering strong communication and teamwork skills.
- Research: Conduct research on cutting-edge tools and methodologies in data science, AI, and defense applications, applying what you learn to ongoing projects and refining your knowledge base.
- Documentation: Learn how to document processes, results, and workflows effectively, contributing to team knowledge-sharing while honing your technical writing skills.
Preferred Qualifications and Learning Objectives:
- Preference for candidates with a military background, who can bring unique insights into the warfighter's perspective and the challenges they face.
- Currently pursuing or recently completed a Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Mathematics, or a related field with opportunities to apply your academic knowledge in a practical setting.
- Basic familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, or scikit-learn), with guidance provided to enhance your skills through hands-on work.
- Knowledge of statistical analysis, data mining techniques, and model validation methodologies with opportunities to deepen your expertise in real-world applications.
- Proficiency in Python (with experience using libraries such as Pandas, NumPy, and Matplotlib) with support to develop your coding skills in the context of data science.
- Familiarity with SQL or other database query languages, with opportunities to improve your ability to handle large datasets and optimize query performance.
- Experience with data generation or simulation tools (such as GANs, synthetic data frameworks, etc.) is a plus, but not required—this internship offers the opportunity to learn these techniques.
- Strong analytical skills and attention to detail, with the chance to apply and refine these skills through data analysis and model development.
- Strong communication and collaboration skills, with opportunities to grow in a multidisciplinary team environment.
Why Join Us:
- Be part of a team of seasoned veterans who have successfully transitioned from the battlefield to the forefront of AI development. You’ll work on projects that have a direct impact on mission success at the tactical edge.
- Gain valuable hands-on experience in data science, synthetic data generation, and machine learning, with the chance to apply your skills in meaningful, impactful ways.
- Develop your expertise in a dynamic environment, guided by professionals who have faced the challenges you’re helping to solve.
- Enjoy flexibility that supports your learning journey, while working on innovative projects that directly address real-world warfighter challenges.
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.