Analytical Mechanics Associates, Inc. (AMA) is proud of our diverse and dynamic work environment and our employees' career satisfaction. We are committed to advancing research across multiple domains and are cultivating a focus on machine learning and generative AI systems. Currently, we are working on developing Retrieval-Augmented Generation (RAG) systems and implementing cutting-edge research into practical solutions. AMA offers a collaborative and innovative environment where interns will work closely with experienced engineers and researchers to tackle complex challenges in AI. 

AMA Labs (AMA’s internal research division) is looking for an intern to support the development of RAG systems and research validation during Spring 2025. This internship will provide hands-on experience in building and optimizing AI models, turning research into code, and validating the latest findings in the field of machine learning and artificial intelligence. This is a 10-week internship located at AMA's offices at NASA Langley Research Center in Hampton, VA, with the possibility of remote work. 

Compensation range: $21- $29 hourly

Responsibilities: 

• Collaborate with the engineering team to build and optimize retrieval-augmented generation (RAG) systems for scalable, efficient querying and response generation.
• Analyze and validate cutting-edge research papers in machine learning, AI, and related fields.
• Assist in turning research publications into working code, experimenting with various architectures, and benchmarking performance.
• Document workflows, experiments, and system improvements for internal and external communication.
• Participate in brainstorming sessions to explore novel approaches to RAG and AI model improvements. 

Requirements: 

• Pursuing or having attained a BS (or higher) in Computer Science, Data Science, Engineering, or a related field.
• Familiarity with Python and libraries such as PyTorch, TensorFlow, or Hugging Face.
• Basic understanding of machine learning concepts, particularly in natural language processing (NLP).
• Experience using Git for version control, including branching and squashing commits.
• Strong analytical skills and interest in reading and interpreting research papers.
• Ability to work independently and collaboratively in a distributed team environment. 

Desired Qualifications: 

• Not all desired qualifications are necessary or expected from applicants.
• Tasks will be assigned based on applicant’s interest, niche skills, and strengths.
• Experience or interest in learning about RAG systems.
• Familiarity with large language models and frameworks like LangChain.
• Prior research experience through coursework, projects, or internships.
• Strong written and verbal communication skills, especially in presenting technical concepts.

Candidate must be a US Citizenship or Permanent Resident.

Analytical Mechanics Associates (AMA) is proud of our customer relationships, our diverse and dynamic work environment, and our employees' career satisfaction. AMA is a small business with a wide reach; headquartered in Hampton, VA, AMA has operations in Greenbelt, MD; Huntsville, AL; Dallas and Houston, TX; Denver, CO; and Mountain View and Edwards Air Force Base, CA. With over 60 years of experience, AMA specializes in aerospace engineering, science, analytics, information technology, and visualization solutions. AMA combines the best of engineering, science, and mathematics capabilities with the latest in information technologies, visualization, and multimedia to build creative solutions.

AMA is committed to the professional growth of every employee, understanding that the successes of our employees drive our success. We provide a work environment that is engaging, collaborative, and supportive. To learn more about our company, please visit our website at www.ama-inc.com and follow us on Facebook and LinkedIn.

AMA is an Affirmative Action/Equal Opportunity Employer and does not discriminate against any applicant for employment or employee because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic prohibited under federal, state, or local laws.