As an AI Engineer Intern, you will join our innovative AI research and development team to work on cutting-edge, impactful real-world AI challenges. You will collaborate with experienced AI researchers, machine learning engineers, data engineers, and data scientists to design, develop, and implement advanced machine learning models, including large language models to deliver scalable and transformative AI-driven solutions. This internship offers the chance to apply theoretical knowledge to real-world, high-impact AI projects and receive hands-on technical mentorship and career development support from industry-leading experts.
This is an entry-level, 10-week, full-time internship expected to begin in June and end in August. Work will be hybrid (minimum 2x per week) from our Reston, VA office. Pay is expected to be $32 per hour. At this time, we are unable to provide housing nor relocation assistance for this position.
What you will do:
- Contribute to the AI lifecycle:
- Support the end-to end AI product development process, encompassing data acquisition, preprocessing, model design, training, optimization, deployment, monitoring, and evaluation to ensure scalable and robust solutions.
- Assist in all phases of the machine learning lifecycle, including data collection, preprocessing, model development, optimization, deployment, and evaluation.
- Develop machine learning models:
- Design, develop, and train advanced machine learning models, including deep learning and large-scale models, to address complex challenges in domains like natural language processing (NLP) and Generative AI.
- Build and train machine learning models, including deep learning models, to solve complex challenges in areas such as natural language processing (NLP), computer vision, or generative AI.
- Analyze large datasets:
- Conduct exploratory data analysis and advanced feature engineering on large-scale, semi-structured datasets to uncover actionable insights and enhance model accuracy and efficiency.
- Perform data analysis and feature engineering on massive, semi-structured datasets to extract meaningful insights and improve model performance.
- Engineer robust software:
- Develop high-quality, production-ready code in languages such as Python, Java, C++, R, JavaScript, along with a good understanding of common AI development frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn while actively participating in system design discussions, code reviews, and testing to ensure robust and maintainable software.
- Write clean, production-level code in languages like Python and C++, and participate in design sessions and code reviews to ensure software quality.
- Research emerging technologies:
- Research and prototype cutting-edge AI and machine learning methodologies, including advancements in areas like explainable AI, federated learning, or multimodal models, while keeping abreast of the latest research and industry trends.
- Help research and prototype new AI and machine learning techniques, staying up-to-date on the latest advancements in the field.
- Collaborate across teams:
- Partner with cross-functional teams, including product or project managers, data engineers and scientists, and software engineers to refine project requirements, align on objectives, and deliver innovative, high-impact AI-driven solutions.
- Work closely with cross-functional teams, including product managers and other engineers, to define project requirements and deliver high-quality technology products.
Basic Qualifications
- A minimum of 9 credit hours of completed graduate-level courses in Computer Science, Machine Learning, AI Engineering, Data Science, or a related technical field.
- A completed bachelor’s degree in computer science, Machine Learning, AI Engineering, Data Science, or a related technical field.
- Candidate must be a US citizen, reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S. per contract requirements
Preferred Qualifications
- A strong foundation in core computer science concepts, including object-oriented design, data structures, algorithms, and complexity analysis.
- Proficiency in at least one general-purpose programming language, with a strong preference for Python.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Demonstrated experience with large-scale datasets and data preprocessing.
- Excellent problem-solving, communication, and collaboration skills.
- Experience with version control systems like Git is a plus.
- Perks of working with us
- Mentorship: You will be paired with a dedicated mentor to support your growth and development throughout the internship.
- Hands-on experience: Gain valuable, practical experience working on impactful, real-world AI projects.
- Learning opportunities: Access training resources and workshops to enhance your technical and professional skills.
- Networking: Build valuable connections with a community of world-class scientists, engineers, and visionaries.