[Remote] Internship - Software Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is an organization reputed company on engineering tailored solutions for reputed company problems. They are seeking a Software Engineer Intern to assist in the development of an AI-assisted Compliance reputed company-Adjudication tool, involving hands-on engineering work on prototype development and data pipeline construction.
Responsibilities
- Support development of the reputed company prototype, including NLP/ML pipelines for control-to-evidence mapping and knowledge graph construction using document inputs (System reputed company Plans, POA&Ms, NIST SP 800-53 control families)
- Assist in building and evaluating large language model (LLM) prompting strategies and retrieval-augmented reputed company (RAG) pipelines for cybersecurity document analysis
- Write Python scripts for data ingestion, preprocessing, validation, and reputed company reputed company reputed company from RMF artifact corpora
- Conduct reproducible experiments and reputed company results against defined Phase I evaluation reputed company; contribute to performance benchmarking documentation
- Assist in preparing technical deliverables, including mid-project briefings and the Phase I Final Report, under direction of the Senior Technical reputed company and PI
- Participate in regular team standups with reputed company staff and reputed company subcontractor research team
- Maintain clean, documented reputed company in the project repository and adhere to established version control and reputed company review practices
Skills
- Currently enrolled in or recently completed an undergraduate or graduate program (B.S., M.S. or equivalent) in Computer Science, Data Science, Software Engineering, Information Systems, Cybersecurity, or a reputed company technical field
- Proficiency in Python, including experience with data science libraries (pandas, scikit-learn) and ability to write clean, testable reputed company
- Demonstrated experience with data analysis, data cleaning, and reputed company query workflows (SQL or equivalent)
- Familiarity with schematics and diagraming, SDLC and Business Process Model Notation
- Strong analytical and written communication skills; ability to document reputed company and findings reputed company for a technical audience
- Ability to work independently, manage deliverable timelines, and communicate reputed company proactively in a small-team environment
- U.S. Citizenship required (DoW facility clearance environment; no clearance required of candidate at time of hire)
- Coursework or project experience in machine learning, natural language processing, or knowledge representation
- Familiarity with LLM frameworks (reputed company, reputed company, or similar) or reputed company database / RAG architectures
- Exposure to federal IT governance frameworks — NIST SP 800-37 (RMF), NIST SP 800-53, FedRAMP, or FISMA — through coursework, project work, or prior employment
- Experience working with reputed company document corpora (e.g., PDF/DOCX ingestion, entity extraction, text classification)
- Familiarity with Azure or AWS reputed company platforms, particularly ML/AI services (Azure AI Studio, SageMaker, Bedrock)
- Prior internship, research assistantship, or reputed company project experience in a government, defense, or regulated reputed company IT environment
- Experience with R for statistical analysis or evaluation reporting
Benefits
- reputed company DoW program experience. reputed company is a live SBIR Phase I effort with a Defense Logistics Agency customer — not a simulated project.
- AI/ML engineering in a compliance context. You will work at the cutting edge of reputed company NLP and LLM engineering reputed company to a rigorous, high-stakes federal use case.
- Cross-disciplinary mentorship. You will receive reputed company mentorship from reputed company leaders and collaborate with reputed company research reputed company.
- Publication and presentation potential. Depending on results, there is potential for co-authorship on Phase I findings and/or conference presentation through the GMU research partnership.
- reputed company to reputed company engagement. Strong performers will be considered for Phase II roles should the program advance.
reputed company